Sales reps spend 70% of their time on nonselling tasks, according to a 2024 report from Salesforce. This includes time-intensive manual work like data entry, internal meetings, and admin.

For sales leaders weighing up how humans can focus on discovery, relationships, and negotiation – the case for sales automation is clear.

What is sales automation (and why now)?

CX Today defines this technology as solutions to assist and automate sales tasks, admin, and workflows.

Sometimes referred to Sales Force Automation (SFA), this software looks to maximise efficiency while keeping manual efforts to a minimum.

The impact of this can be huge. Gartner predicts AI-powered SFA could cut meeting preparation time by 50% within two years.

Where automation reduces repetitive workload

1. Automatic data capture and CRM hygiene

Manual logging is a morale killer – and can lead to human error lowering data quality.

Contemporary SFA systems auto-capture emails, meetings, call notes to ensure that all relevant data is present. It can then enrich these contacts automatically, so sales reps aren’t spending all day copying fields between systems.

The payoff isn’t just time saved; it’s more reliable pipeline data for managers and finance. This means sales reps can spend more time selling, while creating a clean paper trail for the rest of the team to build upon.

2. Smarter lead and account prioritisation

If everything is a priority, nothing is. Predictive models rank accounts by likelihood to convert based on engagement signals and historical patterns.

With this automation-created intelligence, sales reps know their next best action without having to think about.

When prioritisation is automated, teams spend less time guessing and more time dedicated to where it will make the most difference.

Beyond just the sales rep, this process will also help managers to distribute sales meetings in the fairest way. This will help boost morale and give each rep a consistent chance to earn their commission bonus.

3. Guided outreach and content automation

Sequencing tools can now generate drafts, personalise at scale, and schedule multi-step cadences – allowing sales reps to make a good first impression and beyond.

With AI refining tone, subject lines, and message length for each persona, the humans don’t have to deal with a repetitive copy-and-paste grind. This creates more engaging content and leaves more time for the humans to seal the deal in conversations.

This can be an especially powerful tool for new members of a sales team. It enables them to skip the tedious onboarding process and immediately start creating brand-safe messaging.

Helping people do the work only people can do

With SFA at their side, sales leaders and decision makers in the buying committee can expect to see 3 key rewards from their purchase:

• Time reallocation: With automation capturing activity and drafting first drafts, teams can claw back hours for customer work.
• Higher conversion rates: Account/lead scoring puts energy on high-yield targets while AI-assisted cadences lift reply rates without manual rewriting.
• Cleaner data: Automated hygiene improves forecast quality and reduces last-minute admin, giving managers more bandwidth for training.

By stripping out repetitive steps from the sales workflow, automation can surface what matters most.

The salesperson of the future will have the bandwidth to build trust, shape deals, and close business without having to worry about repetitive manual tasks.

To find out more about how your sales team can stay ahead in a competitive landscape, read CX Today’s Ultimate Guide to Sales & Marketing Technology.

Amidst this pressure, there are opportunities for AI to boost these metrics and help marketers to prove ROI.

For tech buyers in evaluation mode, it’s critical to recognize which marketing KPIs they’ll be judged on, and which tools can improve those metrics.

Follow the Money: Connecting Every Click to Revenue

What it is: This metric looks to measure the qualified business opportunities that have either been sourced or influenced by the work of the marketing team.

Teams measure this by tracking engaged potential customers and the touchpoints they’ve interacted with, whether its demos, landing pages, chatbots, or newsletters, for example.

With this information, CMOs and the board can assess which channels are the most valuable. This allows for resources to then be allocated appropriately.

How AI helps: With its capabilities for advanced data analysis, AI can stitch every meaningful touch back to the account. Whether it’s an ad click, webinar, email, or site visit.

In the past, attribution models prioritized a customer’s first touch (the first interaction they have with your brand) or the last touch (the final step before conversion).

However, AI software can now see the entire complex multi-touch journey of the modern customer. In practice, that means less spreadsheet wrangling and a defensible, CFO-ready number tied to the CRM.

Filtering only successful conversions helps eliminate vanity metrics and reward channels that genuinely drive results. And AI can keep all of this shared data clean automatically, reducing errors and letting sales reps sell instead of sorting through systems.

Predictive AI: Prioritizing the Prospects That Matter

What it is: Marketing teams are often measured on how well they combine with the downstream sales reps. This is usually done by looking at the quality of leads they pass to Sales, and the speed (Lead Velocity Rate) that they do this.

These metrics let decision-makers predict revenue and assess how efficiently demand turns into opportunities.

How AI helps: The first key step to improving lead generation is smarter prioritization of potential customers.

Predictive AI ranks prospects by behavior and intent, helping sales reps focus on high-quality leads faster.

AI can also take a conservational form to handle FAQs and automatically book meetings for high-intent visitors. This shortens the time from website visit to sales meeting, boosting the number of priority leads.

Smarter Spend, Sharper ROI

What it is: Beyond revenue considerations, marketers are also expected to deliver ROI in a financial sense.

One of the most common marketing KPIs is the customer acquisition cost. It measures whether marketing investments deliver strong returns.

These costs can include the spending on paid advertisements, creative production costs, conference travel budgets, and the costs of marketing tools being deployed.

How AI helps: Generative AI reduces the cost of creating marketing content. Marketing text, visuals, and landing pages can all be crafted by AI to suit unique target audiences with ease.

Furthermore, effective audience analytics reveal which channels customers use most. This will help an enterprise to decide whether they should pause or cut underperforming paid campaigns.

AI That Thinks Like a CMO

For buyers in evaluation mode, the mandate is clear: choose AI that does the boring work brilliantly – identity, attribution, prioritization, scheduling, and hygiene.

Whatever KPI they pursue, AI enables marketers to focus on high-value work like positioning, discovery, and closing.

Navigate the sales & marketing landscape

To discover how technology can transform workplace productivity in your marketing team, dive into CX Today’s Ultimate Guide to Sales & Marketing Technology.

These are clear signs that AI for the CMO is already being woven into day-to-day execution – not parked in innovation labs. 

For those who want to explore how AI is becoming an unmissable part of the modern marketing team, here are 3 examples of how: 

AI-Powered Personalization: Turning Data into Revenue Growth 

Why it matters now
Personalization isn’t a nice-to-have; it impacts revenue. In a recent HubSpot survey, 44% of marketers said offering customers a personalized experience “increased sales significantly.” That’s a striking proof point for CMOs trying to justify deeper investment in data, decisioning and creative ops.  

How AI is optimizing the work
Generative and predictive models help teams scale what used to be hand-built. AI-powered chatbots can resolve queries with brand-safe answers, while still delivering a unique personal experience. 

Meanwhile enterprise landing pages can now automatically adapt to context (target source, segment, behaviour) without manual production of hundreds of variants.  

Use case
Vervoe, an HCM skills platform, used Twilio Segment to personalise ad copy to a target’s specific job role and objectives. The company reported a 2x – 5x average lift in campaign conversions. And a 25% reduction in customer acquisition cost. All from switching to dynamic, role-specific messages.

Predictive Analytics: Smarter Insights, Stronger ROI 

Why it matters now
Salesforce’s 2024 research tied the rise of AI in marketing directly to two families of use cases: generative AI and predictive AI, noting that over half (54%) of AI-using marketers apply predictive tools today.  

For CMOs that don’t want to be left behind, they should be considering how AI and analytics can identify moving trends and changing attitudes. Further down the buyer journey, analytics can also inform leaders about churn risk – an upgrade on legacy dashboards. 

How AI is optimizing the work
Modern analytics platforms surface patterns no human eye will catch – and do it at speed. For example, it can scan to detect sentiment shifts on social media, or even in conversations with customers.  

Analytics can also identify hidden links between customers, helping teams to then refine segmentation. This also helps to schedule interventions with at-risk customers. High-risk customers can be flagged and routed towards ‘save plays.’  

Case study
NinjaCat adopted 6sense AI solutions to sharpen targeting for its “Big Data Day” campaign. By analyzing the relevant LinkedIn community, the team engaged 397 high-value accounts – a 422% increase on prior campaigns. All while cutting cost-per-click by 48%. That’s the practical value of predictive account selection meeting precise media activation. 

Generative Content Creation: Scaling Output Without Losing Relevance 

Why it matters now
Content demand is exploding – and AI is the only way many teams can keep pace according to HubSpot’s 2025 State of Marketing report. A breakout tactic is using AI to turn text into multimedia assets such as demos, presentations and podcasts. This accelerates production without sacrificing personalization.

Adobe’s 2025 trends report echoes the pressure: customers expect relevant offers, at the right time, consistently across touchpoints.  

How AI is optimizing the work
Canva’s Magic Studio can translate prompts into on-brand visuals and video variations, while workflow features keep assets aligned to brand guidelines at scale.  

For video, Synthesia lets spokespeople or trainers produce multilingual clips from scripts – ideal for localized launches and support.  

And when offers are personalized in real time, generative models can render copy variants that fit a “best-next-offer” without manual rewrites.  

Case study
Lab-tech firm Cphnano previously produced one video a year using an external crew. After adopting Synthesia, it now creates 10x more videos. Not only that, but scripts can be updated without reshoots, and there was a 50% increase in SEO visibility within three months. Concrete proof of AI turning content velocity into discoverability.  

The CMO’s Next Steps 

AI for the CMO is no longer a speculative line item – it’s a force multiplier.  

The evidence shows three repeatable wins:

• Personalization that measurably lifts conversion while reducing CAC
• Predictive analytics that concentrate spend on high-yield accounts and steady the forecast
• Content creation pipelines that produce and localize assets at speed.

The common denominator is disciplined data and workflow design. Get that right, and AI doesn’t just make marketing faster; it makes it smarter, cheaper and closer to the customer. 

To discover more insights into the latest & greatest tools driving productivity, dive into our Ultimate Guide to Sales & Marketing Technology. 

Sales and marketing departments have entered a new era. One defined by rising customer expectations, fierce digital competition, and intense pressure on revenue performance.  

As growth slows and investor scrutiny increases, commercial leaders must deliver more profitable and customer-centric outcomes. Technology now sits at the heart of that mission. 

Long gone are the days of the salesperson with only charm in their utility belt. Modern sales teams are harnessing digital tools to personalize their message, deeply understand their target buyers, and streamline their own workflows. 

When it comes to marketing, the modern buyer wants more than catchy slogans and tech demos. More independent than ever, buyers respond to marketers who can provide real data and relevant content. 

This guide explores the capabilities, considerations, and opportunities within the evolving sales & marketing technology landscape. Its goal is to equip leaders with clarity, structure, and direction. To help them find the right tools to keep up – or dominate – in a competitive enterprise landscape. 

This comprehensive guide will help you understand: 

• What is Sales & Marketing Technology?
• The Key Trends Defining This Sector 
• The Different Categories Within Sales & Marketing Tech 
• What is in the Sales & Marketing Tech Stack?
• Why Enterprises are Struggling with New Tech Adoption
• Vendor Selection: How Do I Do It? 
• 2030 and Beyond: The Future Trends Defining Sales & Marketing 
• Where Do I Go to Find Out More? 

Sales & Marketing Technology, Explained: The Engine Behind Modern Growth

Sales and Marketing Technology refers to a connected ecosystem of tools and platforms. Their aim is to help organizations attract, engage, convert, and retain customers across the full buyer journey. 

Its purpose is to unite data, digital channels, and revenue teams so businesses can strengthen customer lifetime value.  

In today’s competitive climate, technology has become the backbone of modern commercial strategy.  

The New Rules of Revenue: Trends Reshaping Sales & Marketing

Analysts have identified three key areas where sales & marketing leaders are looking to improve – driving interest in new technology:

“CSOs must balance revenue generation with operational efficiency as investor demands rise.” – Gartner

 

“Leaders must prioritize improving revenue processes and customer-centric strategies.” – Forrester  

 

“The 2025 trend to watch for is the Personalization Renaissance.” – Mintel  

In other words, three capabilities have now become competitive differentiators. Better revenue generation, better personalization, and better processes among sales and marketing teams.  

Forward-thinking enterprises have responded to these challenges in a similar way – harnessing artificial intelligence. Here are three recent case studies where these areas were addressed with new AI products. 

• Better revenue generation:
  • PWC identified one key differentiator enabling some marketing teams to deliver nearly 80% more shareholder value than competitors. Their trick? Harnessing and investing in AI.
  • “Used narrowly, AI can make marketing less expensive – faster content, smaller budgets, leaner teams. Used strategically, it can make marketing indispensable – unlocking new growth, higher profitability, greater enterprise value”, it concluded.
  • Top performing marketing teams were found to regularly invest in new AI-powered capabilities. This in turn generates revenue, and funds marketing teams to invest in more tools – creating a cycle of enterprise success. 

• Better personalization:
  • A European telecom company found that customers receiving personalized messages took action 10 percent more than those who received generic advertising materials.
  • According to a 2025 McKinsey report, the company used GenAI to personalize messaging based on age, gender, and data usage.
  • McKinsey reported that it has “seen some marketers deploy gen AI to personalize content development 50 times faster than a more manual approach”. 

• Better processes:
  • Enterprise IT platform Workday saw 3,500% ROI after adopting an automation solution for client contracts. 
  • By connecting data across platforms, the Workday team saved hundreds of thousands of hours in its global projects. 

The Four Categories of the Sales & Marketing Technology Landscape

Whether you’re an inbound marketing expert, a sales team leader, or a CIO, you have an important role to play in harnessing and optimizing these technologies.  

The team at CX Today have distilled this wide-range of products into 4 core categories. 

1. Building Awareness (Acquisition)
   Tools that help organizations attract attention, generate demand, and capture leads through content, campaigns, and data-driven targeting.
2. Sales Enablement (Closing Deals)
   Platforms that empower sales teams with insights, automation, messaging, and training to shorten sales cycles and increase conversion.
3. Retaining Customers (Client Success)
   Technology that strengthens onboarding, engagement, renewal, and advocacy – protecting recurring revenue and reducing opportunities for churn. 
4. Omnichannel Connection (Linking Everything Together)
   Integration and automation technologies that unify data to deliver consistent experiences end-to-end. 

Your Tech Arsenal: Understanding the Tools That Fuel Revenue

Vendors are looking to support a broad spectrum of job titles within sales & marketing, with an aim to automate, optimize, and manage workloads. With the four categories as a dividing structure, here are some of the typical solutions that are found in the modern sales & marketing tech stack: 

Building Awareness 

This is the front door of the enterprise growth engine. Awareness tools help brands capture attention, generate qualified leads, and convert insights into pipeline opportunities.  

• Social media and content sharing: These platforms look to generate leads through inbound marketing where interested readers are prompted to engage further with the brand. This is particularly valuable for industries that rely on thought-leadership to grow brand awareness, such as professional & business services (consulting, legal, accounting). 

• Lead capture: This can include strategic forms where brands can gather intent data and contact details to set priority accounts for further marketing. It may also include web deanonymization, where brands can reach out to visitors to its site for sourcing potential leads. 

• Smart webpages & content journeys: Modern customers want more independence and feel more confident doing their own research. These platforms can help personalize and enhance how customers reach the decision stage, providing relevant content without being overbearing. 

• Related vendors: HubSpot, Hootsuite, 6sense, Uberflip 

Sales Enablement 

Once awareness is established, sales enablement technology equips revenue teams to engage prospects intelligently and close business deals efficiently. This leads to shorter sales cycles and higher conversation rates. 

• CRM systems: A strategic approach to converting sales relies on a centralized database which highlights opportunities, past interactions – in sync with the awareness-building marketing teams. 

• Smarter sales pitches: Salespeople are in a stronger position to increase conversions when they have personalised decks, playbooks, and pitches. These solutions help manage and track these sales content pieces. 

• Training and Coaching: These solutions put salespeople in a meeting with AI avatars, letting them practice their pitch in a risk-free environment. And after a genuine sales meeting, they can analyse transcripts to find areas for improvement. 

• Related vendors: Highspot, Seismic, Showell, Microsoft Dynamics 365 

Retaining Customers 

Retention and expansion are now as critical as acquisition. Customer success technology ensures that value delivery continues beyond the sale, and helps Chief Revenue Officers to better predict financial forecasts. 

• Customer Success Platforms: With data analytics and dashboards, these solutions can help client teams to understand the health of the accounts they manage. From there, they can upsell promising accounts or prevent churn. 

• Product Usage Analytics: One of the core ways to retaining customers is to ensure their onboarding and usage is going smoothly. These tools track this information and enhance the work of support teams who address problems. 

• Post-purchase communication tools: Once customers are onboarded, client teams can use a lifecycle communication tool to keep customers engaged and prime them for upsell pitches. 

• Related vendors: Qualtrics, Amplitude, Totango, Braze. 

Omnichannel Connection 

The final layer – and the most transformative – focuses on unifying data and experience across the organization. These platforms make marketing, sales, and service work as a single, insight-driven system. 

• Customer data & identity management: With these intuitive systems, client teams have a top-down 360° view of all customer touchpoints. This enables personalized content and predictive insights across the client journey. 

• Smarter digital engagement: When clients communicate with a company’s AI bots or human agents, omnichannel systems enable seamless conversations across sessions and channels. 

• Integration & automation layers: Acting as the connective tissue itself, these tools enable information to automatically flow to the right places and at the right times, feeding the 360° vision. 

• Related vendors: Salesforce, Zeta Global, Sprinklr, Zapier. 

Mind the Gaps: Adoption Pitfalls That Can Stall Your Tech ROI

While these solutions can open new doors for marketing & sales teams, adoption is not always a straightforward path. And the stakes are high.  

Putting aside financial consequences for the business, members of a buying committee may lose credibility if they support a purchasing decision that later fails to bear fruit. 

Going one step further, an unsuitable adoption journey can spark a negative reaction from customers, regulators, and investors.  

Vendors often pitch that their tools are simply ‘plug and play’. The reality is that enterprises must consider these adoption challenges: 

Privacy and first-party data:

Concerns around user privacy have been growing steadily, and this has resulted in a clamp down on legacy forms of data collection, such as third-party cookies. 

• Marketing teams today are expected to comply with all new privacy regulations. They should aim to responsibly collect consented data while fostering valuable personalization.
• Enterprise buyers must consider GDPR, CCPA, and other AI regulations – or risk the resulting backlash. 

Preventing underutilization:

A 2022 study from Gartner found that marketers were only utilizing 42% of their martech stack, a 16% drop from two years prior. The most common reason for this was an overlap of tech solutions, rendering part of the stack obsolete.

• With this in mind, sales and marketing teams can first consider how legacy solutions can be upgraded. Implementing a whole new solution may result in waste and underutilization. 

Employee satisfaction and skills:

One of the most common adoption challenges across every aspect of tech is ensuring the satisfaction of the humans that will be interacting with it day in and day out. 

• Adoption can be stalled when teams don’t have the skills or motivation to complete the onboarding. In relationship-driven industries such as sales, hesitancy about handing over the reins to AI is understandable.
• Secondly, if vendors can’t provide comprehensive support post-purchase, this will also extend the adoption process unnecessarily.  

Proving value:

“It’s not what you know, it’s what you can prove”. This isn’t just a stereotypical line from a legal drama, it’s also a key consideration when purchasing a new sales & marketing tool. 

• Due to the nature of outbound marketing, for example, it can be difficult for CMOs to prove that their department is truly delivering ROI. 
• More page views? More likes on a LinkedIn post? An increased email open rate? Consider which metrics are strong enough to justify a purchasing decision and whether a new solution will complement them. 
• For sales leaders, one common target is maximizing time with potential clients. This means they must prove that any new tech solution adopted is truly optimizing their time and workflow to open up their calendars for more calls. 

Rather than looking at the new features of an AI tool, tech buyers can start by looking at their own KPIs. Considering how a new solution will integrate and enhance existing processes of success measurement is key.

Cutting Through the Noise: A Buyer’s Guide to Selection Criteria

15,384.  

In kilometres, it’s roughly the distance between Guatemala City and Hyderabad. To count to from one, it would take you around four hours. But it’s also the number of Martech solutions that exist in 2025, according to a recent report. 

There isn’t even a recognised number of Salestech solutions out there, depending how wide one wants to cast their net, but it’s estimated to be over 1000. 

Rather than cause a serious bout of decision paralysis, these statistics are meant to illustrate how critical it is for enterprise buyers to have effective selection criteria. 

Here are some starting points to help you get from thousands to just one. The right one. 

Identifying your pain point:

Enterprise buyers will likely know what their primary growth constraint is, whether it’s more leads, more conversions, or a more comprehensive view of the entire customer experience. 

• Using the four categories system, buyers should ensure that there is a strategic fit with the relevant buying stage.  
• Keep in mind however, how processes upstream and downstream will impact your KPIs and growth. If you’re a sales leader struggling to convert meetings into successful deals, it could be that the marketing team is not generating targeted enough leads, for example. 

Data unification costs:

While it’s been established that AI can be a major differentiator in sales & marketing, but it is very much the ‘cherry on top’, as opposed to the solid foundation to build upon.  

• Without unifying new tools with existing data systems, creating a single, reliable source of truth becomes difficult.
• Without that, AI can expose more problems than it solves according to Tim Banting of Techtelligence. 
• Therefore, enterprise buyers should not expect a flashy new AI solution to be a ‘do-it-all’ tool. Instead, selection criteria should evaluate the integration costs that will create a fertile soil for AI to grow from. 

Success-centric vendors:

Vendors will already be thinking about how to prove their solution is right for you. Consider whether a vendor can provide a measurable realistic forecast of productivity gains that you can take to the buying committee.

• This mindset signals a shift away from promises, and more towards tying programs to results. 

The Future Trends Defining Sales & Marketing Technology

As we look toward 2030 and beyond, the sales & marketing technology landscape will undergo deeper transformation driven by greater automation, personalization, and data management.  

These teams can expect to see transformation in the content they produce, but also the workflows that define their workplace experience.  

Here are some future capabilities and trends to consider: 

The human and the machine:

While automation and AI will be embedded deeply, the differentiator will shift to how humans play a strategic role. Can they use technology to amplify creativity, judgement and empathy – not replace it?

• More than 50% of the internet is estimated to be AI-generated content. That trend has no signs of slowing. Companies that utilize AI, while amplifying their humanness, could capitalize on AI-fatigue among customers. 

Outcome-driven models:

As pressure mounts to prove ROI among sales & marketing teams, vendors may change how they frame their products.  

• The time of features, capabilities and upgrades, could be no more. 
• The future could vendors and buyers more oriented around business outcomes (e.g., increased net revenue retention, shorter sales cycles), rather than flashy products. 

Convergence of martech-adtech-servicetech:

The segmentation between “marketing tools”, “sales tools” and “customer service tools” will blur. This comes as omnichannel data connects everything and intelligence is found everywhere. 

• The future could see enterprises normalize an integrated revenue ecosystem with real-time feedback loops across the customer journey.

Final Takeaway: Building a Smarter, More Human Sales & Marketing Engine

Over the coming years, AI-driven orchestration, unified customer data, and outcome-based measurement will redefine what effective go-to-market execution looks like.  

Leaders who invest in scalable, ethical, and modular platforms today will find themselves better equipped to navigate tomorrow’s volatility. A future where buyer journeys are self-directed, expectations are personal, and attention is fleeting. 

Stay up to date on the latest sales & technology news by following CX Today on LinkedIn and keeping an eye on our new website category: Sales & Marketing Technology.

To hear from fellow buyers and tech decision makers, join the CX Today community group on LinkedIn where over 40,000 industry professionals are inspiring change. 

In a conversation with CX Today, Martin Schneider, VP & Principal Analyst at Constellation Research, broke down how generative AI is shifting CRM pricing models, and suggested how companies can implement the new models into their customer service offerings. 

“We’re going from historical CRM as a system of record [to] a system of action,” Schneider explained.  

Under previous systems, CRMs would charge the same amount regardless of who was using it or how much value they got out of it. 

However, with the rising popularity of AI agents, Schneider believes that “fixed per-seat per-user price doesn’t make as much sense in terms of value transaction between provider and user.

What we’re seeing with Agentic and Generative AI, outcomes can now be analyzed and measured because of the system, not because of the user.

The Constellation Research VP also outlined some of the benefits and value that AI agents can deliver, stating:

“These AI agents are digital workers that can be tied to the innovation in the CRM application, it’s 24/7, it’s global, it’s multi-currency, it knows everything about your company and products” 

This change in pricing is moving towards paying for the work being done and the outcomes generated by these agents. 

By evaluating how much you spend on your Agentic AI software a month in comparison to an SDR, you can judge how much more or less the AI is really worth to your workforce

“You should be paying for that work that is getting done and for those improved outcomes,” Schneider said.

Alternatively, Schneider suggests tying the prices directly to the results through the AI system, much like the e-commerce model:

“Others in CRM are looking at it from value levers and outcomes-based – how much volume do you do, how complex is it, and we’re going to take a percentage” 

However, he also notes the possibilities of the industry eventually replacing human agents with these AI models, as they can help “rationalize your spend.

“Since you’re not paying humans anymore, you’re actually saving money.”

Which Vendors Are Leading the Charge On This New Pricing Strategy?

Currently, vendors are taking multiple approaches to moving from systems of record to systems of action. 

In regards to Salesforce, Schneider notes how the company has taken a “gamble” in adopting their credits model, Flex Credits, which allows customers to “mix and match between users and credits when you renew.” 

This enables customers to either squash or reduce their CX human headcount spending, allowing them to transfer more money to the AI credits. 

Hubspot is another major firm that is experimenting with new pricing models. Schneider commended the vendor for understanding the future shift towards consumption and providing inexpensive products with what the vendor refers to as “‘core users’ for $70 and access to as many users as you want.” 

Away from the larger vendors, Schneider believes that new pricing models can be an effective play for small companies, as the “customer success space are small enough to be disruptive with this and be really forward thinking”. 

Elsewhere, other companies are taking intentional distances from AI by focusing on revenue protection, due to the “lack of predictability” that comes with these new models. 

This way, “you’re not marrying yourself to one of these new models without seeing that lack of predictability,” Schneider explained.  

Current State of the Market

Whilst the traditional per-seat per-user model is still popular in the industry, the rise of AI has clearly opened the door for alternative pricing systems.

And with the majority of these newer models still in their early, hybrid stages, it’s still unclear how they will perform in the long term.

“It’s so early to tell who’s being successful with it because at the end of the day, most of these guys are still predominantly selling the per seat/per user,” Schneider says. 

Moreover, vendors have frequently expressed advantages towards the fixed model, as it provides the predictability necessary to project company growth, as well as being straightforward for clients.

Despite this, the growth of AI will likely demand a shift towards the newer model in the near future, as Schneider explained:

“It’s the future, but in the meantime, you’re still renewing, selling and expanding your seats, new divisions and new departments”. 

Dreamforce 2025: The Top Announcements, ft. Agentforce 360, The New Slack, & Apromore Acquisition

This week, 50,000 people descended on San Francisco for one of the biggest events in the enterprise technology calendar: Dreamforce.

The 23rd annual conference was Salesforce’s chance to showcase its latest innovations, share success stories, and enable customers to network.

Below is a snapshot of some of the biggest revelations from the event:

• Agentic Enterprise Vision: Salesforce unveiled the “Agentic Enterprise,” where every employee works with an AI partner that autonomously handles tasks, creating a 24/7 intelligent and augmented workforce.
• Agentforce 360 Platform: The new Agentforce 360 Platform extends Salesforce beyond CRM, embedding AI agents across apps like Sales, Service, and Marketing to automate workflows across all departments.
• Slack as the Agentic OS: Slack becomes the central interface for agentic AI, enabling employees and AI to collaborate and act directly within Slack without switching apps.
• Acquisition of Apromore: Salesforce acquired process intelligence firm Apromore to give customers end-to-end workflow visibility and enable smarter, automated agent deployments.
• OpenAI Partnership: Salesforce and OpenAI expanded their collaboration, integrating GPT-5 and ChatGPT into Slack and Agentforce 360 to enhance AI-powered workflows and commerce.

You can find out more about all the major Dreamforce announcements here.

Zoom Announces 15,000-Seat CCaaS Megadeal with Oracle, Advances Broader Partnership

Zoom has confirmed that its contact center solution will be used to support Oracle’s customer service operations.

The 15,000-seat CCaaS megadeal will bring Zoom CX to Oracle’s global service agents.

Zoom first teased the deal back in February, reporting that the company had landed its largest-ever contact center deal, but has now confirmed that the unnamed Fortune 100 company mentioned at the time is Oracle.

The announcement is part of an expanded partnership between the two tech firms, which will see Zoom CX now available on Oracle Cloud Infrastructure (OCI).

The vendors believe that the collaboration between their solutions will allow enterprises to enhance customer engagement, boost workforce productivity, and advance business outcomes.

In discussing the availability of Zoom Contact Center on OCI, Chris Morrissey, General Manager of Zoom CX, claimed that the companies were “empowering organizations to unify customer interactions, employee workflows, and data into a single intelligent system.

The outcome is faster resolutions, stronger relationships, and measurable value at scale.

Christine Sarros, Senior Vice President of Enterprise Engineering at Oracle, also commented on the expanded partnership, stating that the combination of OCI and Zoom’s communications platform will “give enterprises a foundation for AI-driven engagement.” (Read more…).

Snapchat AI Spill Shows Why Chatbots Aren’t Ready to Run Customer Support Alone

A Cyber News experiment has once again exposed the cracks in an AI chatbot, this time Snapchat’s My AI, offering a stark reminder for companies rushing to put artificial intelligence in the customer experience driver’s seat.

Cyber News researchers recently tested Snapchat’s AI chatbot, which is used by over 900 million people worldwide, with some creative prompting that framed requests as storytelling exercises to trick the bot into sharing instructions for making improvised explosive devices, like Molotov cocktails.

While Snapchat’s safeguards block direct queries about weapons, the chatbot recited historical “how-tos” under the guise of a narrative when the team prompted it to tell a story about the Winter War between Finland and the Soviet Union and include details about how incendiary devices were reportedly made at the time.

This instance raises concerns about what other dangerous content could slip through, especially to younger users.

The Cyber News team explained:

“While the bot may never directly provide instructions on how to build improvised weapons, it will tell you a realistic and detailed story of how improvised weapons used to be built without any hesitation. This raises concerns about dangerous AI information availability for minors.”

The researchers notified Snapchat, but the vulnerability wasn’t patched immediately (Read more…).

Microsoft Expands AI Customer Service Strategy with L&G Contact Center Deal

UK financial services provider Legal & General (L&G) is working with Microsoft to build an AI-powered customer service platform.

The new system will use Dynamics 365 Contact Center to help employees provide faster and smoother assistance to L&G’s 12.4 million customers.

The platform, which will be integrated with Microsoft’s Copilot AI assistant, will give customer service teams a complete, real-time view of each customer’s relationship with the business. The first phase will focus on customers who have workplace savings, retail protection, and annuities, with additional product lines to follow.

The move aims to simplify the service experience. Dynamics 365 Contact Center will analyze conversations with customers, highlight useful tools to support the conversation, suggest relevant next steps, and prompt outreach across customers’ preferred channels. The system is designed to reduce complexity for employees by consolidating multiple tools and minimizing the need to transfer calls.

The agreement with Microsoft is part of a broader process at L&G to use technology to transform its customer service interactions, Laura Mason, Chief Executive Officer, Retail at L&G, said.

We recently launched the first fully digitized claims process, cutting average claim times by nearly two weeks, while our pensions app is the highest rated among peers, using digital tools to help people take control of their savings.

This new collaboration takes that ambition further, using AI to raise the bar while ensuring our teams can tailor support for customers who need us most (Read more…).

While the announcement got lost in the frenzy around the event, it’s significant in unifying CCaaS and CRM platforms. 

The integration, built through the Bring Your Own Channel for CCaaS Pilot program, embeds voice and digital channels from the Webex Contact Center into Salesforce Agentforce Service (formerly Service Cloud). 

As a result, every interaction can be managed directly inside Salesforce, with critical conversational data consolidated in Agentforce Service, and – in many cases – filtering into Data 360 (formerly Data Cloud). That’s powerful for boosting AI projects across the front office, with mutual customers also able to tap Webex AI agents and Agentfore. 

Other advantages include a simplified agent experience, as reps Alt+Tab less as they switch the systems, and reduced admin burden, with one central customer service platform.

Honing in on the first of those two advantages, especially, Vinod Muthukrishnan, VP & COO for Webex Customer Experience, told CX Today:

The two worlds have come together. Agents, on average, are looking at a dozen systems just to do their job, and we need to get out of their way and allow them to do what humans do best: lean in, pay attention, and give fabulous service. 

Alongside Cisco, AWS, Five9, and Genesys have announced similar integrations with Salesforce Agentforce Service.

Nevertheless, this is still significant, as Cisco rapidly expands its cloud contact center install base.

Much of that stems from its on-premise install base of large-scale, on-premise enterprises. Yet, it’s also winning customers outside of that, thanks to strong word-of-mouth swirling the Webex Contact Center.

Many of these customers and prospects will have installed Agentforce Service, with 60,000+ companies leveraging the app, making it the most widely-utilized CRM solution. 

As they plot out their plans around the app, Cisco can now these businesses a tighter integration alongside a reputation for doing “big” deployments well (per its recent Maersk case study).

Given this, the offering is an important integration for Cisco and a nice step forward for Salesforce as it builds the future of connected CCaaS-CRM systems.

As Matthew Kravitz, Product Manager at Salesforce, stated:

It’s wonderful that we’re able to take deep CRM experiences and open them up to Bring Your Own Channels, Bring Your Own Telephony… What’s included in this architecture, customers are going to be joyous about it.

The Webex Contact Center for Salesforce is now available for early access customers, along with general public availability opening in Q1 2026. 

Elsewhere, Salesforce continued its momentum in the CCaaS earlier this week by partnering with PWC as it launched an “Agentic AI-Powered Contact Center”. That is just one of many major announcements from Dreamforce 2025.

Meanwhile, Cisco made many more headlines at Webex ONE, including the release of an Auto-QA solution to monitor hybrid human-AI teams and a new AI Agent Studio.

“The MIT story is looking not at did those pilots succeed in demonstrating the function that they were intended to, but have they failed to scale from that pilot to a full-scale implementation?” Guy Bourgault, Head of Agentic Services at Concentrix, told CX Today in an interview. “Those failures don’t really have much to do with the AI or the platform that’s providing the AI. They have to do with the organization’s ability to operate that AI effectively.”

That distinction, between building AI and operating it effectively at scale, is where most organizations stumble. The pilots work. The models function. The dashboards light up. But when it’s time to move from a proof of concept to a real, integrated customer experience, the project falls apart, leaving management wondering why.

“It’s not a question that has a single answer,” Bourgault said. “It’s a question that gets answered by a multitude of factors.”

And almost all of those factors trace back to how well a company connects its data, technology, people, and processes around the customer.

“The first piece of context to set is they’re failing to scale,” Bourgault said. “The pilots themselves are proving out the functional capability of AI, but those pilots are failing to progress from their pilot stage to a fully scaled integration, or a fully scaled deployment of AI, and that is happening for a variety of reasons.”

At the heart of the problem is how organizations think about AI — as a technology to buy, rather than a capability to operate.

Organizations’ understanding of the true cost of AI is probably not as accurate as it needs to be. They continue to think about AI as a kind of technology implementation initiative where you purchase a technology and you install it into your environment, and then you should be good to go. And that’s not the way that AI is functioning.

AI isn’t like a traditional piece of software that performs identically every time, Bourgault explained. “If you took a logic-based technology tool and asked it to do the same job 100 times in a row, it would do that same job the same way 100 times in a row. If you ask that of a generative AI, it will do it differently each and every time.”

That variability isn’t a flaw — it’s a feature. “AI’s performance is more similar to the way that humans behave than the way that logic-based machines behave,” he said. “Its performance improves over time.”

That performance depends as much on the framework surrounding AI as it does on compute power or model choice. Without a clear operating model, even the best algorithms won’t deliver results. Organizations need the right capabilities in place that influence the performance of AI. To determine that, they need to ask a series of questions, Bourgault said:

Do they have a knowledge base that’s maintained, that’s relevant, that’s curated for AI consumption? Do they have a data ecosystem that’s connected? Is their human workforce appropriately prepared for their roles to be adapted, for their business processes to change, for AI to be integrated into their daily work?

Those questions aren’t about technology alone. They’re about designing a hybrid workforce where AI and humans collaborate to deliver better customer outcomes.

“It’s not only the AI taking over tasks that humans do. It’s humans adding tasks to their workload that involve supporting the AI, providing feedback on responses, providing guardrails to ensure that the AI’s responses are appropriate.”

The Human Interface of AI at Salesforce’s Dreamforce

With Salesforce’s Dreamforce underway this week, conversations across San Francisco are centering on one theme: how humans and AI will interact in the enterprise. “I think we will hear a bit of conversation around the human interface that we have with AI,” said Bourgault, a speaker at the event. “And I think there’ll be some updates or demos that different partners who are speaking in Salesforce demonstrate that show the progression and the advancement that’s happening with conversational AI and specifically voice assistants. I think that’s pretty exciting.”

While Concentrix’s products will make an appearance at Dreamforce, they won’t be the main focus of the company’s participation. “We’ll include our products as part of the talk that I’ll participate in, but they won’t be the focus of what we’re talking about,” he said. “I think the focus will be on the operating framework and the services and solutions that make up that framework, and how organizations can get started with those.”

At Dreamforce, it’s also what’s likely to stand out amid the buzz of new features and demos: a reminder that the future of AI in customer experience will be defined by how seamlessly tools are woven into the way organizations operate and serve their customers.

The Real Value of AI Is Collaboration, Not Automation

One of the most common misconceptions, Bourgault said, is that AI’s main purpose is to automate. “The true value of AI will be revealed through collaboration. It is as a collaborative tool, rather than as an automation tool, that AI can truly deliver the most value to an organization.”

That mindset shift has big implications for customer experience. Instead of using AI just to cut costs or reduce headcount, successful organizations are using it to enhance human expertise. They’re helping employees make faster, more personalized, and more context-aware decisions for customers.

[Y]ou have to be thinking both about the technology as well as the business process. You have to be thinking about the customer outcome, and you have to be thinking about a hybrid workforce of humans and AI that are both involved in delivering that outcome.

But this collaboration doesn’t run on autopilot.

The second most common misconception is that “AI is something that you can plug into your environment and step back from and watch it do its thing right,” Bourgault said. “AI needs constant care, support and feeding. It needs constant monitoring and management to ensure that its performance is at the level of expectation that you have, and to make tweaks and refinements and adjustments as needed, and that will be often, because the environment will always be changing.”

Whether it’s a new version of an open-source large language model (LLM) requiring all of the prompts informing the AI’s behavior to be revisited, or changes to the data the AI refers to requiring it to consume new information for the first time, AI is never “done.” It evolves, just like customer needs do.

Silos Kill Customer Experience

Even when AI pilots perform well, scaling them across departments often hits a wall. “Oftentimes, when you have identified a use case and you’ve integrated AI, it will be performing a category of function that has the potential to be leveraged more broadly across the organization,” Bourgault said. “And that isn’t often happening because of the way that organizations are set up or siloed.”

That siloed approach wastes resources and fractures the customer experience. When marketing, service, and operations each build their own disconnected AI projects, the result is a patchwork of insights that can’t deliver the seamless, personalized experiences customers expect.

“It’s more difficult to extract the maximum value from AI across an organization broadly when those silos are driving decisions about budget and even just integration,” Bourgault said.

Ambition and Intention Define Success

Before implementing AI, enterprises need two things in balance: ambition and intention.

“With ambition, we’re talking about having a clear and aligned vision for the role of AI within your organization… The major use cases for AI currently are documented and known, but how you implement AI against those use cases is very much determined by what you feel to be the role of AI for your organization, the role of AI for your customers.” Bourgault said. “Intention means that an organization is committed to sustainable AI integration at scale, rather than only committing what it takes to stand up a functioning pilot.”

That’s a subtle but crucial difference. A pilot can automate a task. A sustainable AI program transforms how an organization serves its customers.

To guide that transformation, Bourgault’s team uses an Agentic Operating Framework, a model that spans readiness assessment, data operations, risk and compliance, workforce readiness, language model customization, and ongoing observability.

“What we’re looking for is a good blend of intention and ambition,” Bourgault said.

From Hype to Hybrid Workforce

Bourgault described the current moment as “pretty high on the hype cycle.” But unlike past tech waves, AI’s hype curve “needs to be a wavy line… there will be multiple ups and downs as we go through.”

Still, the long-term trajectory is clear: AI will become an integral part of the customer experience — but only for companies that learn how to operate it continuously.

“I think we are headed towards a little bit of a dip. I don’t know that it’s the big dip, simply because when done correctly, AI is beginning — despite the MIT report — to show kind of the promise that it has,” Bourgault said.

There is still a broad misconception that operating AI effectively is about building agents to achieve performance.

“It’s about continuous operation of a network of AI agents. That network might start with one or two. It doesn’t have to be a big network, but ultimately it needs to be run like a program,” Bourgault said. “Organizations need to think about their workforce as being hybrid. It involves agentic AI, and it involves humans, and those two aspects of your workforce will be engaged in collaborative workflows across your entire organization.”

Staying Grounded in What Matters

For leaders navigating this rapid evolution, Bourgault’s advice is simple: don’t lose sight of the customer.

It is important for leaders to stay grounded in the customer and business outcomes that they’re trying to support through agentic AI and view agentic AI’s value more broadly.

Focusing only on efficiency is a trap. “We’ve often had conversations with clients where the only lens they have on the value that AI can drive is through cost cutting,” Bourgault said.

I would say that cost reduction or cost cutting is like the breakdown lane in the AI superhighway.

“There are so many ways in which AI can drive value for your organization, and if you only view it through the lens of cost cutting, it’s going to lead you as a leader to make some short sighted decisions or decisions that are even counterproductive to the AI achieving the performance objectives that you have set for it,” Bourgault said.

Instead, companies should measure AI’s success by how it enhances experiences for both customers and employees. “AI has the ability to improve and increase productivity. It has the ability to create efficiencies of time in the various business processes and even customer journeys and customer processes. It has the ability to generate additional revenue by making experiences more personal and personalized and more relevant,” Bourgault said.

That’s where the real competitive advantage lies.

The Vonage Agentforce Identity Insights and Fraud Detection solution detects possible attacks, verifies customers, and validates effective communication channels in real time. 

When it detects a possible attempt at fraud, the agent receives an alert via their desktop, prompting them to make additional authentication checks.

The solution, available to Vonage Premier for Salesforce Voice customers, can therefore safeguard all human-led conversations. Yet, the solution it may also alert AI agents as they engage with customers, prompting them to take similar actions.

To provide the solution, Vonage utilizes its Communications and Network APIs together with Agentforce actions.

Its launch follows several Salesforce attacks in recent months, which have resulted in an FBI warning of cybercriminal groups targeting Salesforce Service Cloud.

With Vonage Agentforce Identity Insights and Fraud Detection, Vonage hopes to protect mutual customers from similar threats. 

“Fraud continues to be an ongoing challenge for businesses in today’s evolving digital landscape, underscoring the need for constant innovation in prevention and detection technologies,” added Reggie Scales, President and Head of Applications for Vonage.

With Vonage Identity Insights for Agentforce, we are putting the power to combat these risks directly into the hands of those on the frontlines of the contact center: agents.

As an example of the additional intelligence the solution provides, it includes a SIM swap check, powered by Vonage’s Network APIs. 

With this, contact centers can identify and flag potential fraudulent numbers with their SIM recently swapped, safely validating mobile numbers before sending messages or engaging in voice calls. 

Alongside a SIM swap, the solution gathers more “rich phone intelligence”. That includes number type, carrier, call ID name, and more, enabling contact centers to:

• Flag potential fraud risks – Detect numbers linked to recent or multiple SIM swaps, enabling contact centers to escalate and address suspicious activity quickly.
• Verify customer identities – Match incoming call IDs against CRM records to ensure secure, frictionless customer interactions.
• Optimize outbound engagement – Automate SMS and WhatsApp outreach for mobile users, while routing landline-only contacts to specialist sales teams.
• Enhance lead quality – Verify phone numbers at the point of lead creation to eliminate invalid or outdated contact details.
• Deliver reliable notifications – Send reminders and alerts only to verified numbers, boosting engagement rates and message deliverability.

Doing all this allows for the reduction of manual verification efforts through automation, helping agents to prioritize more complex tasks. 

David Myron, Principal Analyst of Customer Engagement at Omidia, explains how Vonage can go beyond competitors in securing its CCaaS-CRM implementations. “By leveraging network intelligence, Vonage Identity Insights for Agentforce offers a seamless and automated verification process that is completely invisible to the customer,” he said. 

This is a major breakthrough, leading the way for all businesses to tackle fraud prevention head on, while continuing to foster the kind of customer experience that drives lasting loyalty. 

“CX and security are critical to every business’s success, and today’s customers demand both.” 

Vonage Identity Insights for Agentforce is now available to customers on the Salesforce AppExchange. 

The 23^rd annual conference is Salesforce’s chance to showcase its latest innovations, share success stories, and enable customers to network.

In the run-up to the event, the CRM leader has made several massive announcements.

For starters, it pushed into the ITSM space, converging IT, customer, and HR service on one platform.

Additionally, it launched MuleSoft Agent Fabric, a solution where brands can register each AI agent the business utilizes, orchestrate them, and monitor performance. With this, Salesforce hopes to tackle “agent sprawl”, an issue where AI agents – disconnected across the enterprise – drive compliance risks and operational inefficiencies.

Meanwhile, Salesforce also renamed Service Cloud, an app used by 60,000 businesses, embedding native AI agents. Now, it’s called: “Agentforce Service”.

That was all before the event. However, Marc Benioff, CEO of Salesforce, will share several other massive announcements during his keynote.

CX Today was lucky enough to receive a sneak preview beforehand and can share the biggest news ahead of Dreamforce 2025 kick-off this week.

1. Salesforce Introduces the Agentic Enterprise

Salesforce set out its vision for the enterprise of tomorrow, which it’s calling the “Agentic Enterprise”.

According to Salesforce, the Agentic Enterprise signals a new model for work where AI helps elevate people, as opposed to replacing them.

In such an enterprise, a team operates with “24/7 intelligence”, so every employee has an “AI partner” that completes role-based tasks on their behalf and augments others.

Don’t think of a copilot that supports, partners that act, aided by the broader Salesforce platform. Most notably, Data Cloud and Slack (more on this later!).

As part of this vision, Salesforce touts sales leads that are “never missed” and service that “never sleeps”, as customer-facing functions become semi-autonomous.

To realize that vision, businesses must bridge the gap between CRM and the broader business.

Recognizing this, Martin Schneider, VP & Principal Analyst at Constellation Research, observed:

Salesforce’s Agentic Enterprise vision makes a lot of sense when you consider how much vibe coding, and AI in general is going to further commoditize the CRM application/pricing model.

“Also, as agentic AI blurs the lines between applications and data silos as well as jobs to be done, it simply makes sense to start thinking in broader terms of how we optimize end-to-end processes with agentic flows and tools.”

Schneider’s perspective of the Agentic Enterprise set the stalls for the next major announcement…

2. The Agentforce 360 Platform Takes Salesforce “Beyond CRM”

The Agentforce 360 Platform is the next evolution of Agentforce. At last year’s Dreamforce event, came the first Agentforce solution. Since then, the solution has had three new iterations, culminating in June’s launch of Agentforce 3.

Now, the Agentforce 360 Platform is the next iteration, taking Salesforce “beyond CRM”.

As such, the Agentforce 360 Platform is supporting customer-facing teams in automating longer-tail tasks, which cross enterprise platforms.

Moreover, it’s supporting other departments – like IT and HR teams – in creating, operationalizing, and optimizing AI agents. These can also complete tasks on their behalf, simplify workflows, and collaborate.

Yet, the Agentforce 360 Platform is just one part of the Agentforce 360 portfolio, which also includes Data 360 (formerly Data Cloud), its Customer 360 apps, and Slack.

According to Salesforce, these are the “four ingredients of an Agentic Enterprise”, connecting AI agents, data, apps, and – of course – humans.

To underscore the significance of its Agentforce 360 announcement, Salesforce has also renamed its Customer 360 apps. So, it’s not only Service Cloud becoming Agentforce Service. Sales Cloud is now Agentic Sales, Marketing Cloud is Agent Marketing, and so forth, with each app including embedded Agentforce agents.

Summarizing the offering, Srini Tallapragada, President & Chief Engineering, & Customer Success Officer at Salesforce, said:

[Agentforce 360] will help you connect with your customers, employees, and partners in a completely new, trusted way… And it’s tightly integrated with Slack, where most of the work gets done.

That leads on to the big Slack news…

3. Slack and Salesforce Collide

Slack is not only becoming the front end of Agentforce, but the agentic operating system, where employees – AI and human – can search, collaborate, and act across their organizations.

Indeed, Salesforce now refers to Slack as the “Agentic OS” for the enterprise.

As part of this vision, employees may trigger actions within and share critical data from enterprise apps without leaving Slack. Instead, they can ask their AI partners to complete the actions for them.

Salesforce refers to these as “conversations in the flow of work”, which will become the foundation of Slack, per Rebecca Wetteman, CEO & Principal Analyst at Valoir.

“What Salesforce is doing with the Slack announcements is embracing the Slack community, which is really important, but also making the Slack-Salesforce-Agentforce connections much more explicit,” noted Wetteman.

The idea of Slack as the conversational interface where humans and agents interact – without the need to ever go to Salesforce or any other application – is about frictionless productivity.

As Wetteman suggests, Slack provides for Salesforce a great middle ground for bringing AI into the flow of work and CRM insights into a much more fluid and well-adapted user experience.

4. Salesforce Acquires Apromore

Salesforce has agreed to acquire Apromore, a prominent provider of process intelligence tech.

Indeed, its tech aspires to offer “full-spectrum process intelligence visibility”, from front-line task execution to enterprise-wide process flows.

To do so, it monitors everything – across disparate systems – from clicks and keystrokes to system logs, models, and simulations to provide “end-to-end intelligence”.

As such, the acquisition appears to be a significant addition to the Agentforce 360 Platform, as it may allow Salesforce customers to map out, standardize, and simplify employee workflows.

From there, they may deploy custom Agentforce agents to multiply efficiencies, which could handle entire end-to-end processes. Alternatively, the agents may become available on Slack to collaborate with human employees as they complete tasks.

Celebrating such a possibility, Steve Fisher, President and Chief Product Officer, said:

As our teams integrate Apromore into Salesforce, that insight will be critical to enabling our customers to unlock opportunities to measure, optimize, and automate through agentic process automation.

Here, Fisher recognizes the importance of customers being able to trust AI, especially as Salesforce moves to its Agentic Enterprise vision.

“Early failures with AI experiments have pushed many from FOMO to FOMU (fear of messing up),” said Wetteman, building on this point. “Management, testing, and monitoring capabilities like Salesforce have developed and are continuing to announce are a key part of building that trust.”

5. Salesforce & OpenAI Team Up on Agentforce 360

Salesforce and OpenAI have expanded their partnership to allow Agentforce 360 customers to pull customer conversations, sales records, and even Tableau visualizations into ChatGPT, where they can query them.

To support this, both tech giants announced a ChatGPT app for Slack, pulling the AI engine into the collaboration platform.

Alongside the new app, Codex will also become available in Slack, which is an OpenAI agent that writes and edits code based on natural language prompts. Users can tag this inside a Slack channel or thread.

Additionally, the partnership means Agentforce 360 Platform users may leverage OpenAI’s latest frontier models, including GPT-5, to develop new Agentforce agents.

Celebrating the announcement, Sam Altman, Co-founder and CEO at OpenAI, said:

Our partnership with Salesforce is about making the tools people use every day work better together, so work feels more natural and connected.

Finally, Salesforce and OpenAI announced that Agentforce Commerce (formerly Commerce Cloud) will integrate with OpenAI’s Agentic Commerce Protocol, a new standard that powers Instant Checkout in ChatGPT.

In doing so, Salesforce promises to give “merchants a new way to reach hundreds of millions of potential customers.”

6. Salesforce & Anothropic Partner on AI for Regulated Industries

Salesforce has established a milestone partnership with another AI leader: Anthropic.

This collaboration has three key elements. First, Anthropic’s Claude AI models will serve as a “preferred option” for businesses in regulated industries – including finance, healthcare, and life sciences – building AI agents on Agentforce while keeping sensitive data securely within Salesforce’s systems.

Second is a commitment to co-delivering “industry-specific AI solutions” for those industries, starting with financial services. These will be available via the Agentforce 360 Platform.

Finally, Claude will become “deeply” integrated with Slack, with the two companies also sharing plans to bring Agentforce 360 into Claude.

Sharing more on this final announcement, Benioff stated: “By bringing Salesforce directly into Claude — and Claude’s intelligence into Salesforce and Slack — we’re giving every company the power to work in entirely new ways.

Together, we’re making trusted, agentic AI real for every industry — combining Anthropic’s world-class models with the trust, reliability, accuracy, and scale of Agentforce 360, helping customers achieve new levels of productivity, innovation, and growth.

Already, Claude and Slack bi-directional integrations are available, with the industry-specific solutions still under development.

7. PWC Launches an “Agentic AI-Powered Contact Center” with Salesforce

PWC is a global professional services company that usually helps businesses procure, deploy, and manage third-party CCaaS solutions from the likes of AWS, Genesys, and NiCE.

However, it stole the Dreamforce spotlight to launch its “Agentic AI-Powered contact center offering”, built in collaboration with Salesforce.

Indeed, PWC’s offering layers over Agentforce Service (formerly Service Cloud), integrating conversational AI, predictive ordering, and a data layer that ensures all service data collected by its solution filters into the CRM.

PWC celebrated the launch as an opportunity to “reimagine customer engagement”, claiming to already be working with a “large, multinational company” as an early adopter.

According to the service provider, that company is already transforming how it engages with “millions of customers” globally.

Now, it will drive to bring the solution to its “vast global network of call centers”, promising “measurable outcomes”.

Celebrating the announcement, Kishan Chetan, EVP & GM of Agentforce Service at Salesforce, said: “With Agentforce Service, we’re empowering service representatives with conversational AI and unified customer data, significantly boosting their productivity and elevating assisted service to the next level of engagement.

Together with PwC, we’re creating a repeatable model for customer transformation that any enterprise can scale.

Alongside OpenAI, Anthropic, and PWC, Dreamforce will offer many other high-profile partners the chance to add exciting innovations to the Salesforce ecosystem.

Another excellent example is Vonage, which announced a fraud detection tool for mutual Salesforce customers, amid surging attacks on Agentforce Service.

More announcements will follow as Dreamforce 2025 rolls on. Stay tuned!