By integrating Microsoft 365 products into the software company’s platform, Zendesk customers can access Agent 365 capabilities for intelligent productivity. 

In turn, Microsoft has implemented Zendesk Agent within 365, allowing its customers to access tools to enhance service productivity and workflow efficiency. 

Craig Flower, Chief Information Officer at Zendesk, highlighted how the partnership expansion would improve Zendesk’s ability to deliver a superior customer experience. 

“Our collaboration with Microsoft on Agent 365 and Zendesk Agent for Microsoft 365 Copilot is a pivotal moment for Zendesk,” he explained. 

“This collaboration not only solidifies our position as a leader in enterprise AI automation but also ensures that Zendesk remains at the forefront of the evolving digital worker landscape.  

“By integrating with Agent 365 and Microsoft 365 Copilot, we are empowering our customers with both autonomous and streamlined support capabilities, optimizing operations, and ultimately delivering a more efficient and reliable employee experience within Microsoft 365.” 

Improving Service Experience 

This partnership aims to upgrade small business experiences by implementing both tools to generate tailored needs. 

By establishing Microsoft Agent 365 within Zendesk’s platform, the AI offers autonomous ticket management support for Zendesk’s customers for reduced human intervention. 

These capabilities include ticket creation, handling, status monitoring, and communication management within Microsoft’s environment to ensure data governance requirements are met. 

This allows human service agents to shift away from constantly reviewing routine queries and return to high-demand, complex tasks. 

In return, Zendesk Agent has been integrated into Microsoft 365 Copilot to support its core apps with ticketing capabilities, such as ticket submissions, status monitoring, and following up tasks without the need to switch tools. 

Similar to the first integration, this capability is managed within Microsoft’s environment, resulting in limited friction for tool management and deployment.  

As a result of the integration, agents can experience direct AI-assisted support in several routine task areas, resulting in higher responsiveness, resolution, and reduced waiting times. 

This AI integration allows smaller businesses to elevate their service demands to the level of any well-established company, including delivering higher productivity and service levels. 

By implementing these tools directly within a business, teams can manage their workflows effectively without agent intervention. 

Furthermore, both tools offer customers secure and compliance management for handling adoption risk within a governed ecosystem. 

Targeting The Small Business Market 

The integration follows a similar trend in recent months of larger vendors trying to dominate the small enterprise customer corner by offering tailored products and services to fit their needs. 

Earlier in November, Zoom had secured its commitment to providing service capabilities to companies of various sizes with simple, straightforward tools to enhance their businesses. 

The communications giant notes how businesses with smaller teams require different demands than larger ones, forcing some to juggle various workloads across the board to keep up with demand. 

This means vendors will need to personalize their tools and approaches to cover more ground and advance these smaller businesses to the industry standard. 

This has been a well-documented issue in the CX industry, as various companies have recently eliminated support for enterprise customers that don’t meet their size standards. 

Unfortunately, some customer enterprises that are unable to provide businesses with desirable profit results may be asked to cancel their subscription if the company can no longer provide the services needed or intend to solely focus on its largest customers. 

However, companies such as Microsoft and Zendesk have offered support for this neglected market, supplying these customers with both tools to elevate their teams while prioritizing their unique requirements. 

Srini Raghavan, Corporate Vice President for Microsoft Copilot and Agent Ecosystem, explained how the tool collaboration will offer these enterprise customers support across a range of business needs, and allow them to elevate their issue resolutions even at their current capacity. 

He said, “AI is transforming how organizations deliver employee service, and Microsoft’s collaboration with Zendesk is leading that change by enabling a new era of intelligent support. 

“We’re combining the power of Microsoft 365 Copilot’s intelligence with Zendesk’s modern service platform, enabling employees to resolve IT, HR, and Finance issues seamlessly within the tools they use every day.” 

This approach enables enterprises to access information instantly across various environments, providing their agents with automated, complex responses. 

Deepdesk was previously recognized for its approach at the Microsoft Hackathon Awards in September, winning the highest score among CX vendors in the category ‘Ready to Scale’, strengthening its relationship with Microsoft. 

The Platform-Agnostic AI Approach 

Platform-agnostic AI is an approach that enables AI to operate independently from a platform without the need to rebuild or redesign itself. 

And whilst traditional AI models are typically linked to a single system, Platform-agnostic AI can run seamlessly across different CX platforms whilst maintaining consistency and independence from a single vendor. 

This means that enterprises can function flexibly across multiple environments, such as Microsoft or Salesforce systems. 

In 2024, Deepdesk was acquired by CX provider AnywhereNow to advance its product suite with Deepdesk’s AI assistant tool. 

In conversation with CX Today, Jonathan Quayle, Product Evangelist at AnywhereNow, explained how this approach can operate smoothly across different environments. 

He said, “Platform-agnostic AI means organizations don’t need to rebuild or replace their existing CX infrastructure to benefit from intelligent automation.  

“Instead, it integrates with the existing CX stack – whether that’s Genesys, Salesforce, or a proprietary system – with the AI capabilities, such as Microsoft Copilot, layered on top of it.”  

The Benefits  

This AI layer approach aligns with hybrid AI models, enabling humans and agents to coexist within the same system without replacing one another. 

It enables the AI to support repetitive tasks such as research, response suggestions, summarizing, and automating workflows, while humans remain in the driver’s seat for customer interactions. 

Qualye continues: “Achieving this involves decoupling the AI logic from the underlying architecture, which allows us to orchestrate agent assistance, knowledge retrieval, and automation across environments. 

“This approach allows for consistent performance and context retention, regardless of the platform. It also means organizations retain control over their tech stack, avoiding lock-in and enabling flexibility as their needs evolve.” 

Furthermore, this approach can maintain independence whilst also retaining knowledge and context it received from travelling across platforms, allowing for seamless assistance and optimal agent usage. 

With reduced deployment complexity and expanding human capability, this also helps accelerate integration and ROI even when changes are made to any of the adopted systems. 

He said, “These tangible outcomes directly impact cost-to-serve and customer satisfaction.” 

Microsoft Partnership  

Utilizing its long-standing relationship with Microsoft, AnywhereNow has utilized the CCaaS giant’s Copilot tool in its platform-agnostic customer experience approach, allowing it to deepen its partnership with Microsoft. 

The SaaS provider has leveraged Copilot AI as the engine in its approach, while also still enabling seamless deployment for systems other than Microsoft. 

This utilization only improves willingness to adopt this approach since many organizations already adopt Microsoft tools in their systems. 

Quayle added, “It also provides a trust advantage as governance, security, and compliance conversations have already happened. 

“This gives customers the freedom to choose the tools that work best for them, while still leveraging the benefits of Microsoft.” 

The Challenges

Despite the approach offering seamless flexibility with AI, Deepdesk finds difficulties in ensuring full compatibility at scale. 

This can include issues with enterprises choosing to locate their data sporadically across multiple CX systems, resulting in data gaps for the AI. 

In fact, “The real challenge lies in orchestrating data flows between disparate systems, ensuring that AI can support agents in real time without introducing latency or inconsistency.” 

This can cause havoc if the approach is blocked or not incorporated in all necessary systems, stopping the AI from moving across and accessing the required data to generate responses for agents. 

This may also prove challenging when systems need to be updated or thrown out without including the platform-agnostic model, likely leading to lost context or creating silos. 

The AI layer can only function once it receives a level of understanding and information at a consistent rate, no matter what types of varied technology are being used. 

This requires enterprises that implement this approach to expose the AI to all necessary systems, enabling its agents to receive the best possible responses. 

“Enabling platform-agnostic, hybrid agent journeys isn’t about plugging into existing systems, it’s about designing AI that can operate across fragmented architectures while maintaining continuity, context, and control.  

He added, “Our approach is composable by design, allowing us to adapt to different environments, evolve with changing tech stacks, and preserve the AI investment even as platforms shift.” 

This feature is designed to further the Amazon Connect Email platform, utilizing built-in capabilities that enable agents to deliver quicker response times. 

The workflow tool is the latest addition to AWS’s email and contact center capabilities. 

Released in November 2024, Amazon Connect Email is an omnichannel support feature that enables customer service agents to respond to and divert customer emails all within the same system as voice and chat, allowing agents to handle customer queries in a single space. 

The AI-enhanced email workflow tool enhances Amazon Connect Email by allowing service agents to expedite email customer service through automation capabilities. 

By utilizing large language models (LLMs), these AI-powered workflows can allow Amazon Connect to analyze emails, detect customer intentions, assess potential risks or complexity from the interaction, and evaluate next steps. 

After analyzing the email, the tool will provide a summary of the customer’s profile and any previous activity with the enterprise, the determined query category, and a brief rundown of the email to help tailor the response accurately. 

This tool also grades the received email based on how confidently it understands the message with Amazon Bedrock API and Claude AI, factoring in clarity, tone, topics, risk assessment, and time sensitivity, while also considering whether the customer is part of any premium packages by retrieving the user’s profile. 

This profile retrieval will include the customer’s current credit score, service level, and contact history to help the tool further evaluate the email score. 

After this, the tool implements a two-step process, where the LLM produces binary outputs for each negative factor it recognizes, using an embedded mathematical function to ensure the calculations align with the scoring evaluation. 

Enterprises can also personalize the scoring framework to fit their needs and determine the number of emails routed to an agent. 

Once a score has been determined, the email will receive either a generated response (if the score is 80 or higher) or be routed to an agent’s inbox for a personalized response (if the score is lower than 80), whilst also providing an explanation detailing how the tool determined the score. 

To simplify future interactions, the tool can automatically generate a case detailing the email and information previously gathered, allowing agents to view conversation history from a single place where email handling has occurred with generative AI.  

Agents can also personalize AI-generated responses to keep human intelligence in the loop and can add AI-powered workflows to Amazon Connect Email via Amazon Bedrock. 

What This Tool Means For Customer Experience 

The Amazon Connect AI-enhanced email workflows allow enterprises to bridge the gap between customer demand and agent availability through automating repetitive email tasks and filtering complex queries to agents, providing customers with human responses and agents with enhanced productivity where needed. 

These AI-powered workflows outrun traditional automation systems by understanding context clues behind interactions, including emotion and characteristic human responses by analyzing a customer’s profile. 

This avoids agents from partaking in repetitive research tasks and instead solving complex, human-based problems to deliver solutions that an LLM cannot solve, resulting in higher levels of meaningful work for the agent. 

This also resolves issues with email backlogs, customer survey responses, and agent exhaustion, driving improvements in customer service. 

The communications platform disclosed its Q3 earnings on Monday, highlighting a strong growth from its customer experience portfolio. 

Zoom has also revealed its plans to grow product revenue further by enhancing its existing products with additional AI capabilities to drive AI-first customer experiences. 

During the earnings call, Zoom announced that the platform would be evolving from its traditional customer experience platform to an AI-focused one, aiming to drive productivity and relationships. 

Eric Yuan, CEO and Founder of Zoom, revealed that after its strong quarterly results, Zoom would be able to move forward with this vision. 

He said: “This performance reflects the durability of our business driven by the growing value we are delivering for customers as we evolve from a communications leader to an AI-first platform for work and customer experience. 

“Our vision is to be the AI-first work platform for human connection.” 

Zoom expects to accomplish this transformation by following its three strategic priorities: enhancing its existing products with AI, driving growth in AI products, and scaling AI-first customer experiences. 

Enhancing Existing Products 

During Zoomtopia 2025, the communications platform unveiled AI Companion 3.0, an updated version of AI Companion that utilizes agentic AI not only to respond, but also to act, advising on tasks such as meeting preparations, freeing up time, and call follow-ups. 

Zoom has embedded various AI capabilities and tools, including AI Companion, across its platform foundation, including: 

• Zoom Meetings: Zoom’s AI Companion, a proactive AI assistant tool, offers meeting summaries, follow-ups for next steps, and drives work forward. 
• Team Chat: Rising by 20% in active monthly users year over year, AI Companion supports the messaging product by providing customers with chat summaries, composition tools, and simplified search options for higher productivity. 
• Zoom Phone: This tool now offers Voice Intelligence for call transcription, summaries, noise cancellation, call routing, and analytics and insights for customer data collection, with over 10 million users now paying for Zoom Phone as of early Q3. 
• Zoom Contact Center: Working as Zoom’s cloud-based contact center solution, this platform has adopted AI tools such as Virtual Agent, an agentic AI chatbot offering complex tasks and responses for customers, and AI Expert Assist, allowing agents to utilize AI support in real-time with summaries and translations and offer possible agent responses during customer interactions. 

In fact, AI Companion usage has grown four times year-on-year, revealing that these AI features are seeing value from user activity, resulting in rapid adoption. 

By adding AI to these already-established products, customers are more likely to accept these capabilities once they’ve been integrated into the software. 

Driving Growth in AI Products 

By moving beyond its core communication tools and investing in greater agentic abilities, Zoom offers its customers further access to its AI tools to personalize them to their needs. 

This allows Zoom the chance to drive AI product revenue with product monetization, generating financial growth rather than just adding tools to products. 

In fact, 90% of Zoom’s top CX deals involve paid AI features to contribute to product revenue, offering both subscription and consumption models to suit the customer. 

This includes the development of AI tools such as Custom AI Companion, a paid version of the standard AI Companion model targeted towards enterprise-tier customers, allowing businesses to customize the tool to meet specific demands and policies. 

This also includes similar products such as Virtual Agent and AI Expert Assist, as well as Zoom’s recent acquisition of BrightHire. 

Scaling AI-First Customer Experiences 

Through utilizing tools such as Virtual Agent and AI Expert Assist, Zoom is using AI to transform interactions between customers and enterprises by expanding these products across the platform for automated workflows. 

These tools will involve automating routine requests and advise agents during workflow automation, voice, chat, and video calls for faster results. 

Zoom has also implemented a feature that allows enterprises to install either Zoom’s or a third-party’s AI tool, encouraging them to become familiar with AI usage while tailoring it to their needs. 

This strategy will also involve Zoom working with its largest customers to move AI agents into deployment; however, this may prove difficult. 

During the earnings call, Zoom noted that despite this upsurge in AI tool adoption, its net dollar expansion rate stayed at 98%, 2% lower than expected, likely suggesting that large customers had not been spending as much as hoped on Zoom’s products, with renewals on larger accounts proving difficult to resume. 

Zoom Key Earnings Results 

Zoom’s earnings results showed some strong areas of performance across enterprise and cashflow revenue results 

• Zoom’s total revenue reached $1.23BN, up 4.4% year-on-year 

• Its enterprise revenue grew 6.1%, totalling 60% of Zoom’s total revenue 

• Average monthly churn increased by 2.7%, similar to Q3 2024 

• Its operating cash flow increased to $629MN, up 30% year-on-year 

The update puts unification at the forefront. Addressing the fact that many enterprise teams have to toggle between standalone tools, Zoho aims to deliver something closer to a true operating system.

A Connected Workspace Designed for Frontline Service Teams

The most immediate impact comes from the redesigned interface. Zoho One’s new “Spaces” structure organizes tools by context, whether for personal productivity, company-wide collaboration, or functional areas like marketing, sales, or finance. The value proposition here is to reduce friction.

The Action Panel and unified Approvals take that concept further, pulling tasks, sign-offs, and action items from across the stack into a single view. Customer-facing roles, especially those that handle service escalations and sales cycles, often have to pull data from multiple apps. This approach aims to reverse that dynamic by pushing relevant information to the user instead of the other way around.

Dashboards and the new Boards framework also help consolidate operational and customer-related data. Because Boards can be assembled from Zoho’s own analytics or third-party dashboards brought in through single sign-on, customer support and sales teams can combine metrics, from ticket backlog to deal progression to customer sentiment, within one context.

Unified Integrations for Consistent CX Across Systems

Customer-facing operations typically rely on diverse systems covering ticketing, CRM, commerce platforms, payment portals, and engagement tools. Zoho has addressed this with a stronger emphasis on native integrations and an expanded model for third-party connectivity.

The unified integration panel gives administrators full visibility into Zoho-to-Zoho and Zoho-to-third-party connections, including recommendations for additional integrations.

Raju Vegesna, Chief Evangelist at Zoho, said during a media briefing that limits on integrations are typically dictated by outside vendors:

“There are limits in terms of capability and the exposure of their API… technically, as long as they support some of the standard protocols, it’s fairly straightforward.”

The introduction of a unified portal may have the most impact on customer experience operations. Instead of customers juggling multiple logins for CRM updates, support tickets, commerce orders, payments, and more, organizations can merge all their portals, including those from non-Zoho systems. For large enterprises especially, where siloed customer portals are a known pain point, this consolidation could help improve customer effort scores.

Domain verification, authentication records, and other behind-the-scenes tasks can also now be handled centrally. This includes new support for GoDaddy users, who can authorize automatic updates to DNS records, which is a useful capability for customer service and marketing teams that previously relied on IT intervention.

AI Steps Into a More Contextual Role

AI is deeply embedded in the release through Zia, Zoho’s AI assistant, which has an expanded footprint, and new intelligence hubs. Because Zoho One unifies data from more than 50 apps, Zia can take on tasks that span categories, for example, pulling HR, CRM and support information into a single query.

For example, it can help leaders understand how much time each employee spent with a particular account, Vegesna said, which requires cross-system reasoning not typically possible in isolated applications.

Zia Hubs, now promoted to a standalone application, automatically collects content such as signed contracts or recorded meetings into dedicated hubs. Users can then query that information directly. Vegesna explained:

“All the documents that you put in that hub… you can say, ‘hey, here are the same documents. Show me only the documents that auto renew within the next three months.’”

This could streamline contract renewals, customer onboarding, or issue-resolution workflows by exposing the right information without manual digging.

AI also assists in product navigation. Zia is trained on all 55+ Zoho applications, which means a user can ask how to run an Instagram campaign and be guided directly to the relevant tool, in this case, Zoho Social, and receive recommendations on how to use it, Vegesna noted.

Zia is coming into the status bar of Zoho One. Zia will be able to create and plug in widgets because the data is connected to the back end and powered by analytics. Users will be able to select from preset reports and dashboards and they are organized, whether they are CRM, HR or support related, such as a helpdesk overview, and pinned to the dashboard, Vegesna said.

“Because we have a broad suite of applications that are deeply integrated on our stack, and have the context that enables the intelligence… we are basically embedding [AI] contextually so that the user does not even know that they’re using AI here.”

Ensuring Data Sovereignty and Enterprise Control

Security and data sovereignty are becoming an increasing concern for enterprises as they pay more attention to where AI systems source and store data. Zoho made clear that its ability to operate its own full stack from infrastructure to applications enables deployment models that many competitors can’t match. As Vegesna noted:

“In sovereignty… we are doing these on-premise deployments in some countries where your data center has to be set up in that country, because we own … the entire stack … we are able to do it particularly when dealing with governments.”

The demand for national or regional control is growing, especially in markets where critical communication systems must remain within the country’s borders to comply with data privacy regulations. “They want to own some key aspects. For example, communication … I don’t want someone else to … pull the plug on my communication systems, so I want it on my data center within my country … those have come up a lot, and we are doing those deployments as well.”

Encryption and data governance were also focal points. Zoho confirmed that customers can now bring their own encryption keys and assign them at the application level. “On the security side … customers ask, ‘Can I bring in my own encryption keys and encrypt my data within Zoho?’ And now we are enabling that,” Vegesna said. “They can now select which applications can use what encryption key, and they can define encryption keys based on their specific set of applications, like their documents [and] emails.”

Zoho argues that AI governance, especially around permission systems, has been overlooked in broader industry discussions. Vegesna said:

“B2B LLMs are different from B2C LLMs, because the permission layer plays a very critical role. I think nobody can do a solid AI strategy and implementation if you do not have a directory system in there. And we have been saying it for years, and we are one of the very few vendors who do directly in Zoho, because that has the entire permissions structure in place.”

Cloud directory integrations that enable permissions are a granular level should be at the core of enterprise AI.

“If we do not have a directory system, we cannot say we can do good AI that is well protected, and you should not have access to some data that AI just memorized, because that all has to be under a firewall and the permission system.”

“We own the triple A: authentication, authorization and access control,” Vegesna added.

Together, these capabilities reinforce Zoho’s pitch to enterprises, that unified architecture and control over its infrastructure allow for tighter data governance and deployment models that meet stringent regulatory or geopolitical requirements.

The through-line across the release is the shift away from app-centric work toward context-centric work. This is a change that resonates strongly in customer-facing environments where speed, accuracy, and personalization depend on smooth access to data.

By pulling together dashboards, workflows, approvals, and AI-generated insights from across the business, Zoho One offers a way to reduce employee and customer effort. Functions that are traditionally fragmented, including billing, support, onboarding, and renewals, can be unified at the workflow and data level rather than treated as separate systems stitched together by manual processes.

For enterprises looking to consolidate their customer-facing tech stack without compromising on data control or the breadth of tools, Zoho is positioning the new release as a platform that can serve both operational needs and experience-driven outcomes.

This new partnership will have both companies co-developing AI-focused strategies to market to global customers. 

This partnership will also allow both to expand AI productivity on their respective platforms. 

ServiceNow and NTT DATA have begun their joint plans to market AI-driven solutions, including developing and selling these products to transform how AI is used in the workplace. 

These are set to include various enterprises, commercial companies, and mid-market segments. 

This new strategy emphasizes the companies’ previous partnerships, focusing on their commitments to advise other enterprises to adopt and execute AI into their businesses. 

ServiceNow also intends to use the expanded partnership to place NTT DATA as a delivery partner in its services to guide customers in safely deploying AI-powered automations and enhance operational efficiency. 

Amit Zavery, President, COO, and CPO at ServiceNow, highlighted how this new partnership development will improve AI across businesses, stating:

“ServiceNow and NTT DATA are expanding access to AI-powered automation across any industry and any geography to achieve measurable business impact for organizations at every stage of the AI journey, 

“Together, we’re transforming how the world’s leading enterprises operate, making work simpler, smarter, and more resilient with the ServiceNow AI Platform.”

NTT DATA will be using the partnership to escalate the ServiceNow AI platform to its business to improve its levels of productivity, efficiency, and make improvements to its customer experience across the enterprise, by adopting its AI agents and Global Business Services. 

Abhijit Dubey, President, CEO, and Chief AI Officer at NTT DATA, emphasizes how the partnership can benefit both NTT DATA and other enterprises. He said:

“Expanding our partnership with ServiceNow is a key milestone in our mission to build the world’s leading AI-native services company,”  

“By combining ServiceNow’s agentic AI platform with NTT DATA’s global delivery scale and industry expertise, we’re enabling enterprises to accelerate innovation, enhance productivity, and achieve sustainable growth.” 

Who is NTT DATA?

The technology services company provides enterprises and governments with responsible innovations for cloud, AI, security, data centers, connectivity, and application services. 

This latest partnership allows NTT DATA to access ServiceNow’s generative AI and workflow automation, enabling it to supply improved offerings to its customers by integrating more complex solutions, positioning itself as a leader of enterprise AI transformation within the industry. 

NTT DATA can also use this opportunity to expand its market reach by co-developing AI tools with a well-established company, especially in the US and Europe, where ServiceNow holds strong brand recognition. 

What This Partnership Means

This partnership expansion reflects the increasing intensification of AI-led transformation investments amongst current major vendors. 

The collaboration allows both companies to become more central in their position as leaders in enterprise software strategy development, highlighting to other vendors where they stand to build better relationships instead of developing capabilities independently. 

By fully aligning operations such as products and delivery services, more companies can join the competition and adapt to trends cost-effectively. 

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. 

The next twelve months will test every assumption in customer experience. Economic pressure, rising costs, and cautious spending are pushing CX leaders to prove value faster. 

Tim Banting, Head of Research at Techtelligence, says: 

“The latter half of 2025 and 2026 will be a year of pragmatism.” 

“Enterprises aren’t slamming on the brakes – they’re shifting focus toward tangible benefits.” 

According to Techtelligence data from more than 1,800 organizations, 62% are actively researching or deploying new CX and UC platforms. These companies want measurable efficiency, reduced redundancy, and technology that pays back in time saved, not just promises kept. 

Predictive, Personal, and Human: The New CX Frontier 

An emerging CX trend focuses on evolving from reactive customer service to predictive empathy. Banting explains: 

“We’re seeing AI move from automation toward predictive and personal intelligence. It’s becoming a more empathetic layer rather than a reactive service.” 

Techtelligence data shows over 1,100 enterprises are currently exploring systems that combine automation with emotion-sensing AI to anticipate dissatisfaction before it surfaces. The intent is to retain loyalty in a slower economy where every customer counts. 

However, this personal touch introduces new governance challenges. “You need to make sure your AI is explainable and that your data policies are auditable,” Banting warns. “You can’t just take AI’s word for it.” 

For CX buyers, key evaluation questions include: 

• How does the vendor ensure AI explainability? 

• Is there a unified data layer to fuel the AI’s learning? 

• What metrics show measurable impact on resolution speed or satisfaction? 

Time Capital as the New Resource to Watch 

If 2023 was about ROI,  a CX trend to watch for in 2026 is ROT – Return on Time. “Success is being measured by time given back to employees and customers, not just money saved,” Banting explains. “Time capital will become as valuable as financial capital.” 

This shift reframes efficiency from cost-cutting to time-creation. Shaving seconds off a call or automating back-office tasks compounds across thousands of interactions. Yet Banting cautions against shallow interpretations: “Time saved doesn’t automatically mean it’s used wisely. We should look at how AI helps productivity, not how many employees can be replaced with the time saved”. 

For CX leaders, this is a wake-up call to expand metrics beyond the contact center. True efficiency spans the entire customer journey, from inquiry to resolution. Measuring time across departments – support, logistics, and product – reveals the real impact of AI on business productivity. 

Experience Infrastructure: Where CX Meets UC 

The boundary between customer experience and collaboration is fading fast. “By 2026, unified communications and customer experience won’t be treated as separate categories,” says Banting. “They’ll merge into what we call experience infrastructure.” 

Techtelligence defines Experience Infrastructure as the unified system that connects employee collaboration (UC) with customer engagement (CX). Nearly one in five enterprises are already researching both areas together. 

The logic is simple: internal speed equals external satisfaction. When back-office experts, service agents, and AI tools share data in real time, resolution times shrink, and consistency improves. The outcome is a seamless flow from internal teamwork to external delivery. 

CX buyers evaluating new platforms should ask vendors: 

• Can our UC and CX data layers interoperate natively? 

• How easily can customer-facing insights flow back to internal teams? 

• What governance controls exist across both systems? 

From Testing to Doing: The Execution Era 

Enterprises are done experimenting. “We’re moving from experimentation to execution,” Banting says. “AI and automation aren’t pilots anymore—they’re being scaled for measurable outcomes.” 

Techtelligence’s Q4 2025 Buyer Intent Index shows that 41% of large enterprises are using AI to improve collaboration and 39% are adopting predictive CX tools. This marks a shift from proof-of-concept to proof-of-performance. 

Conclusion: The CX Buyer’s 2026 Playbook 

The next phase of CX maturity will hinge on efficiency, intelligence, and trust – the three benchmarks Techtelligence calls the “enterprise decision-maker’s agenda.” 

To stay ahead, CX leaders should: 

• Invest in predictive AI that understands emotion and intent. 

• Quantify “time capital” across the full customer journey. 

• Demand explainable AI and visible data governance. 

• Align UC and CX investments within an experience infrastructure framework. 

• Prioritize partners that show proof over promises. 

In Banting’s words, “This is really the year of implementation and the year of pragmatism.” For CX buyers, that means acting on insight, measuring in time, and proving value – fast. 

Follow for More Buyer Trends & Insights 

To find Tim’s advice on buyer power in 2026, dive into his article on Techtelligence.

If you’re an enterprise technology buyer or involved in procurement decisions for your business, follow Techtelligence on LinkedIn for weekly insights, analysis, and expert advice to help you make smarter technology choices. 

You can also join its growing LinkedIn Community Group to discuss trends, share experiences, and connect with like-minded business professionals driving digital transformation in their industries. 

The cloud-based software company announced its third-quarter earnings report on Monday, revealing strong results across the board. 

This has led to ongoing investments into current and future AI products and initiatives. 

“We remain on track to exceed the $100MN in ARR from new products by the end of 2025,” said RingCentral CEO, Vladimir Shmunis, adding:

“Adoption of our new AI-led products is broad-based across various customer cohorts, from small businesses to large enterprises.

“Our GSP partners are also beginning to sell these new offerings, expanding our reach and accelerating adoption.” 

This expansion has led the company to roll out multiple AI product releases this week, increasing its customer base by branching out into emerging AI trends. The launches are aimed at enhancing communication experiences for both customers and agents.

This has resulted from an R&D spend of $125MN into its new AI portfolio. The company is already seeing consistent profitable growth, in the hopes of exceeding the year-end ARR target. 

RingWEM Adds AI Workforce Tools to Cloud Contact Center

On Monday, RingCentral released its latest AI product, RingWEM, an AI-powered workforce engagement management suite designed to enhance its native cloud contact center, RingCX. 

The suite offers four capabilities to strengthen customer experience across agent performance, customer satisfaction, and operational efficiencies by using AI-powered insights: 

AI Quality Management: Designed to give human agents the skills to improve their overall performance, the quality management tool will use personalized customer quality criteria to evaluate and provide extensive insight and feedback on customer calls. 

The tool is used to analyze and observe full customer interactions and agent workflows, delivering focused guidance for reskilling. 

Furthermore, the tool offers AI-based coaching recommendations to improve agent expertise, allowing enterprises to improve their workforce by viewing their agents’ performance analytics, common communication themes and advise them on next steps using the provided data-driven advice. 

AI Workforce Management: Used to improve quality in customer service, planning for potential challenges, and overall efficiency, this tool combines precise data forecasting and resourceful scheduling to align staff with probable tasks to tackle targeted demand. 

By using precise data forecasting, the AI workforce management tool can use algorithms to analyze past and current data trends and business drivers to predict the likelihood of contact quantities, allowing time for agents to tackle abnormal spikes before they occur. 

With intelligent scheduling, the workforce tool can generate actionable schedules for agents to follow that include agent preferences, adjustable service level actions, and business requirements to keep agents on track with tasks. 

These can be modified to fit irregular changes in working conditions to ensure that service levels stay the same to avoid customer friction. 

Additionally, customer agent supervisors can run probable scenarios to analyze the effectiveness of staff models and company changes before they are implemented. 

AI Interaction Analytics: This tool provides enterprises with high-level insights into customer satisfaction with interactions, compiling data taken from surveys and summaries from the interactions themselves to address negative customer experiences. 

AI Interaction Analytics can dissect customer conversations through voice tone, language preferences, and patterns in speech to assess satisfaction. 

The tool can use this and other conversations to further analyze key customer trends and issues as a whole, allowing businesses to proactively address these concerns before escalation. 

Screen Recording: Similar to the AI Quality Management capability, this tool allows supervisors to evaluate customer-agent interactions by collectively linking calls and screen recordings for a wider range of information into quality of conversation and workflow efficiency. 

These tools can be utilized to address underlying issues with agent performance and customer satisfaction and elevate operations in contact centers to deliver smarter service. 

RingCentral Debuts Agentic Voice AI Suite

RingCentral has also released its agentic voice AI communications suite, encompassing three tools that enhance communication experiences across the lifespan of each customer interaction. 

AI Receptionist (AIR): Before a conversation begins, this tool ensures that calls are not left unanswered. 

Using the voice AI ability to interact with customers, this AI agent can comprehend a customer’s reason for calling, answer questions, hand off real-time interactions to agents with summarized caller context, and identify and log potential opportunities that may require a human agent to follow up. These can help to avoid customer friction and repeated information. 

For scheduling interactions, AIR provides multi-calendar support across a company to integrate employee schedules and harmonize teams. 

Sales opportunities are collected and stored for future use in Salesforce, HubSpot, or with AIR’s own database. 

AIR can also be used on any SIP-based phone, allowing AI customer handling to be dealt with across the cloud, any premises, or hybrid setups. 

Brian Tucker, Chief Digital Officer at Televero Health, is a customer of RingCentral’s AIR tool. 

He said, “Using RingCentral’s AI Receptionist, the results are undeniable. We saw our monthly appointments increase 14 percent in the first four months, an increase in monthly revenue of over $200,000. 

“That kind of growth and return on investment is exactly what we need.”

AI Virtual Assistant (AVA): During a conversation, AVA can provide an agent with real-time assistance across customer interactions by implementing four key capabilities: 

• Real-Time Calls and Meeting Summaries: Identify the relevant information, questions, and actionable tasks during the span of a call or meeting, generating summaries and highlight reels to allow agents to keep track of the interaction’s objective during the call. 
• AI Writer to Create and Translate Communications: This capability can draft, edit, and translate conversations in multiple languages, allowing for seamless and customer-focused messaging. 
• Multi-Use Assistance Across Workflows: By adapting to a user’s communication method, via phone, text, or chat, this tool can provide intelligent prompts and relevant actions for each task. 
• Product Adoption and Feature Discovery: AVA can advise discovery and management methods to improve RingCentral’s overall customer enterprise experience. 

Kira Makagon, President & COO, RingCentral, explained the value of AVA in an enterprise workflow: “By putting trusted voice intelligence at employees’ fingertips, AVA makes work more productive and empowering,

“AVA is your personal virtual assistant that enables you to work smarter, faster, and more efficiently.”

AI Conversation Expert (ACE): After a conversation, ACE steps in to offer evaluated business insights from these interactions and adds it into one analytics and insights layer for a simplified outlook. 

It provides real-time insight into current customer satisfaction, trends in revenue, and overall agent team performance, giving context to performance data to allow leaders to act quickly. 

When requested, ACE can turn compound data into written summaries, recommend actions and examples of improvement, and be used an interactive interface to allow leaders to inquire related queries with instant results. 

Zach Jecklin, Chief Information Officer at Echo Global Logistics, and customer of ACE, uses the tool for improving company knowledge on customer calls and data trends. 

“AI Conversation Expert provides us with the detailed coaching for individual calls, and the dashboard connects the dots by rolling up all that data into a clear, concise view of the major trends impacting the entire business,” Jecklin said.  

“We used to have call data. Now, we have business intelligence. It’s that simple.”

RingCentral Pairs New AI Tools with Solid Growth

RingCentral has launched the new AI tools in conjunction with the announcement of its strong third earnings quarter. 

During its earnings call, the company reported a total revenue result of $639MN, seeing a growth of 5 percent from the previous year. 

Subscription revenue also increased, rising by 6 percent to $616MN, with a 23 percent rise of $130MN in free cash flow, which it intends to increase during the rest of the year.

AI is everywhere, speeding up processes, automating routine tasks, and promising 24/7 coverage.  

Yet customers and agents still want what technology alone can’t deliver: empathy, connection, and trust.  

That’s the dilemma for leaders in 2025. The challenge isn’t whether to use AI; it’s how to weave it together with human intelligence to create experiences that actually matter.  

Calabrio’s latest research highlights four priorities every contact center should be thinking about. 

1. Closing the Agent Disconnect with Emotional Intelligence and AI

AI is now a near-universal presence in contact centers, with 98% of leaders admitting to using the technology.  

But here’s the twist: 61% also admit customer conversations are getting harder, not easier.

Perhaps it’s because, while powerful, AI sometimes still struggles to replicate the empathy needed in emotional moments. 

That work falls squarely on agents. With bots handling routine queries, human teams are left to tackle the trickiest, most emotionally charged interactions.  

Yet, while leaders say they value empathy, adaptability, and resilience, their actions often don’t back it up.  

Calabrio’s research underlines the problem:  

• 64% of organizations aren’t prioritizing emotional intelligence or social interaction training. 

• 59% fail to provide ongoing coaching for AI-driven workflows.  

• Nearly a third of leaders admit their agents don’t trust AI.  

In short, they talk the talk but fail to walk the walk.   

Given these findings, there’s no surprise that there’s a clear disconnect between agents and leaders.   

Leaders expect agents to shine where AI falls short, but many feel underprepared.  

Closing that gap takes more than new tech. It means investment in coaching, feedback, and skills development that help people bring the empathy customers crave. 

2. Meeting Rising Customer Expectations

Customer expectations aren’t standing still.  

In the modern contact center, customers expect more personalized interactions with faster resolutions at any hour of the day.  

• 40% of leaders say their customers expect round-the-clock service.  

• 36% report rising demand for personalization and speed.   

Little surprise, then, that most centers are leaning on AI.  

A striking 83% believe AI will unlock 24/7 support, while 79% think it will elevate the contact center into a genuine strategic business driver.  

However, technology alone isn’t enough.  

Customer channel preferences are shifting fast. Voice still matters, but digital, self-service, and social are all on the rise.  

More than half of contact centers now offer self-service, and another third are planning to roll it out.

The sticking point is integration, with just 36% of leaders saying they’ve achieved a true omnichannel setup.  

For customers, that means inconsistent experiences. They don’t care about the back-end complexity – they just want things to work smoothly.  

Closing that gap could be one of the biggest differentiators of 2025. 

3. Rethinking KPIs in the Age of AI

While metrics like average handle time and first contact resolution still matter, they rarely tell the full story.  

Contact centers are starting to broaden their KPI mix, with greater emphasis being placed upon agent wellbeing and customer sentiment.  

The most common metrics now include:  

• Performance assessment (86%)  

• Wellbeing score (84%)  

• Bot containment rate (81%)  

• Average handle time (84%)  

The inclusion of wellbeing scores and bot metrics points to a new reality: efficiency KPIs no longer stand alone.  

As AI becomes more central, ‘bot experience’ is as important as customer experience.  

As Magnus Geverts, VP of Product Marketing at Calabrio told CX Today:  

“We measure too many things in the contact center; it makes it hard to see the forest through the trees.”

That comment cuts to the heart of the challenge. Leaders need to trim bloated dashboards and focus on the handful of KPIs that really drive performance, customer loyalty, and agent engagement. 

4. Building an Outsourcing Strategy for Flexibility

Outsourcing is no longer a cost play – it’s a strategic necessity.  

Calabrio found that 79% of contact centers now rely on external partners, and nearly a third are setting aside budget specifically for workload distribution in 2025.  

If done right, outsourcing can bring agility with improved service. It helps centers manage seasonal peaks, balance workloads, and deliver consistent service without breaking budgets.  

But rigid outsourcing models don’t cut it anymore.  

As Geverts explained:  

Contact Centers need to collaborate with their outsourcers on volumes.  

“With the growing interest in outsourcing, it will be integral to give contact centers the necessary help to reach out to their vendors in real time.”

That’s the key. It’s not just about cost – outsourcing partnerships now need to be collaborative, responsive, and ready to adapt in real time. Customers expect fluid, always-on service. Anything less risks leaving them behind.  

The Contact Center of the Future 

AI is reshaping the contact center, but it isn’t a silver bullet.  

The real winners will be the organizations that blend technology with human skill, empathy, and agility.  

For 2025, that means:  

• Automating the routine: Use AI to handle repetitive tasks and free up human capacity for high-value work. 

• Empowering agents: Equip them with tools that provide real-time insights and support. Help them work smarter, not harder. 

• Breaking down silos: Ensure insights from customer interactions are shared across departments from marketing to product to leadership. 

• Measuring what matters: Track how intelligence from the contact center drives business outcomes. 

Those four considerations form a roadmap for contact centers to stay competitive, resilient, and human in an AI-driven world.