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.

Below, we evaluate four leading CX AI providers, comparing their data architecture, model performance and integration maturity – key traits for decision-makers comparing customer experience tools.  

What Matters When Choosing Predictive CX AI 

Before looking into specific vendors, it’s useful first to step back and remember what you need to consider. Below are three factors it’s important to keep in mind: 

Data architecture & consolidation – The ability to ingest, unify and analyse multiple touchpoints (web, mobile, contact centre, social) is critical. Without a real-time data layer your predictions will lag. Building a “vendor-neutral data layer” is increasingly becoming a central piece of the CX tech stack.  In fact, whilst 94% of businesses are investing more in AI, only 21% have fully embedded AI into their operations. 

Model performance & actionability – It’s not sufficient to just surface insights; models must forecast behaviour (churn risk, next-best-action) and feed downstream workflows. AI can anticipate customer needs before they arise by analysing vast amounts of customer interaction data.  

Integration maturity & scalability – Even the most sophisticated models mean little without seamless integration. The best customer experience tools plug into existing systems (CRM, contact centre, ERP) and scale across both geographies and channels.  

Building on these criteria, here are four vendors worth serious consideration in 2026.

NICE Ltd. 

NICE has evolved its flagship customer experience platform into an AI-native environment. It now markets its “Enlighten” engine and the “CXone Mpower Orchestrator” which combine real-time analytics with automation across the customer journey. The company claims to deliver predictive routing and next-best-action engines that trigger human or bot responses depending on customer sentiment and context.

From a data architecture perspective, NICE supports global scalability and voice/omnichannel integration, addressing both model performance and real-time action. While the vendor may come with a legacy contact-centre heritage, its recent focus shows strong alignment with modern CX technology trends. 

Strengths 

• Mature platform with global scale and broad CX footprint 

• Predictive routing and sentiment-based decision making built into live workflows 

• Strong partner ecosystem and integration credentials 

Considerations 

• Because of its breadth, implementation may require more time than niche tools 

• Buyers should validate the “predictive” claims carefully  

Google LLC (Customer Engagement Suite) 

Google has pushed hard into the CX space, driven by its growing range of conversational and engagement tools. It stands out for its ability to detect intent and entity across channels. While most known for conversational AI, Google’s platform also has predictive capabilities – for instance, forecasting contact-volume spikes and routing accordingly. 

Google offers strong cloud-data architecture and granular real-time analytics, giving teams the infrastructure to scale predictive CX models. Organizations with significant investments in cloud-native data stacks will find Google LLC a particularly compelling choice. 

Strengths 

• Cloud-native, scalable architecture with strong analytics underpinnings 

• Strong brand and ecosystem support for advanced data/machine-learning pipelines 

• Good fit where CX AI is part of a broader digital transformation 

Considerations 

• May require additional implementation effort (data-ops, custom models) for full predictive use-case 

• For contact-centre-specific workflows, you may need partner overlays 

Kore.AI  

A rapidly emerging leader in predictive CX, Kore.ai has become synonymous with intelligent virtual assistants that combine conversational and predictive automation. The company’s XO Platform delivers intent prediction, emotion analysis, and autonomous task completion across digital and voice channels.  

Kore.ai’s strength lies in merging dialogue analytics with predictive insights – enabling enterprises to move from scripted responses to proactive engagement. Its open integration framework connects with CRMs, ITSM, and workforce platforms, ensuring predictions become immediate actions. 

Strengths 

• Predictive intent and emotion detection within conversations 

• Low-code interface accelerates deployment and training 

• Flexible integration with existing customer experience tools 

Considerations 

• Still maturing in large, multi-lingual deployments 

• Requires clear governance to manage automated decisioning 

Genesys 

Genesys has re-established itself as one of the top predictive analytics vendors in CX, driven by its AI-powered orchestration layer and “Predictive Engagement” suite. It analyses customer behaviour in real time, from web interactions to voice analytics, then determines the next best action, agent or channel to optimise outcomes. 

Strengths 

• Innovative approach geared toward proactive, autonomous workflows 

• Good fit for organisations willing to experiment and scale up quickly 

• Lighter implementation burden possible 

Considerations 

• Fewer large-scale reference deployments than incumbents 

• Buyer should validate predictive-model maturity, underlying data pipeline and integration readiness 

How to Use This Guide 

At the evaluation stage, your task is to match vendor capability against your requirements. Use this article to: 

• Short-list 2–3 vendors based on architectural fit & strategic alignment 

• Map each vendor to your priority use-cases (e.g., churn prediction, real-time routing, next-best-action) 

• Ask vendors detailed questions about their model performance, integration time, and proof-points 

Key Questions to ask Vendors 

• How is the data architecture structured to support real-time modelling and activation? 

• What actual measurable outcomes (reduced churn, increased NPS, cost avoidance) can you share? 

• How quickly can you integrate into our CRM/contact-centre stack and deliver pilot value? 

• How do you avoid “AI washing” (i.e., vendors re-labelling basic analytics as predictive)?  

Choosing your Predictive CX Customer Service Tools

Ultimately, in 2026, the leading customer experience vendors will be those that pair advanced CX AI with strong predictive capabilities and mature integration frameworks. The four vendors we’ve discussed bring different strengths: whether it’s global scale, cloud-native agility, analytics depth or innovation speed.  

Use your evaluation criteria to match vendor capabilities with your organisation’s needs. With the right decision you’ll move from reactive service to proactive experience – meaning more value, happier customers and measurable business impact. 

Choosing a vendor is just step one. Choosing the right CX strategy is everything. Find out more in our Ultimate Guide to AI & Automation in CX

Companies that once viewed automation as cost-cutting now see it as a growth catalyst. The numbers speak for themselves: AI-enabled contact centres are reducing handling times, boosting efficiency, and driving customer satisfaction (CSAT) to record highs. That means stronger loyalty from your customers and measurable impact for your company’s bottom line.

This guide will help you understand:

• What Do AI and Automation in CX Really Mean?
• Why Reactive CX No Longer Works
• Choosing the Right CX AI Provider
• How to Adopt AI Into Your Business
• Getting Real Results from AI & Automation
• AI & Automation Trends for 2026
• AI Support With a Human Touch
• FAQs
• Your AI & Automation Journey

What Does AI and in CX Really Mean?

AI and automation in customer experience means a lot more than simple scripted chatbots. Today’s AI & automation toolkit includes technologies that learn, reason and orchestrate complex workflows to boost both efficiency and human connection with your customers:

Generative AI: Uses artificial intelligence to create original, personalized content that make customer interactions feel more human and engaging. It helps businesses reply naturally, recommend products, and deliver faster, more relevant experiences.

Agentic AI: Refers to AI systems that can take initiative, make decisions, and perform tasks autonomously to achieve specific goals without constant human direction. This is AI that acts proactively, anticipates customer needs and resolves issues on its own.

Workflow Optimisation: Robotic process automation (RPA), and AI powered summarisation tools streamline repetitive tasks such as data entry, case routing and after-call notes. This frees agents from mundane work, meaning they can focus on the things they do best.

Predictive Customer Insights: Predictive models analyse interaction patterns, sentiment and purchase history to forecast churn risk, recommend the next best action or identify up-sell opportunities. Traditional call centres wait for customers to raise their hands; proactive CX flips that script and predict issues before a ticket is ever raised.

Why Reactive CX No Longer Works

The days of waiting for customers to raise a support ticket are thankfully over. Reactive CX strategies aren’t just outdated – they’re risky. Early warning signals like declining engagement or negative sentiment can now be detected long before a complaint lands. Automation can then send a helpful update, initiate a refund or route the customer to a specialist. Even simple notifications, such as a delivery delay alert, can defuse frustration and build trust between you and your customers.

The Benefits of Proactive Engagement

Proactive CX has a range of benefits. It’s been shown to reduce inbound volumes, lower cost per contact and strengthen customer loyalty. Agents spend less time on repetitive troubleshooting and more time on meaningful conversations. Automating just 20 percent of support tickets can increase repeat purchase rates by eight points, showing that small automations can yield significant returns.

Avoiding Over Automation

It’s easy to get over-excited about the potential for AI automation, but overzealous deflection can push high value customers into self-service loops and miss valuable cross-sell opportunities.

Start by segmenting interactions by value. Automate low complexity tasks, offer hybrid options for mid-value cases and prioritise human agents for high stakes interactions to ensure your customer are getting the best support possible.

Choosing the Right AI Provider

The best CX AI partner isn’t necessarily the one with the flashiest demo, it’s the one that aligns technology with your vision of customer excellence. Look for providers that demonstrate measurable ROI, robust security standards, and a clear track record of success in your industry.

“A reliable CX vendor will offer both scalable infrastructure and human-centred design – ensuring AI tools enhance empathy, not replace it.”

Integration flexibility is critical; prioritise platforms that connect seamlessly with your CRM, analytics, and omnichannel communication stack through open APIs or low-code orchestration.

When comparing vendors, evaluate these four key factors:

Accuracy and adaptability: Assess how often the provider updates its AI models, retrains with new data, and applies techniques like retrieval-augmented generation for grounded responses.

Integration: Confirm the solution can be seamlessly integrated with your existing tools and doesn’t create new data silos.

Transparency and compliance: Check for clear data-handling policies and adherence to privacy regulations like GDPR. This ensures both you and your customer’s data stays safe.

Support and scalability: Ensure the vendor offers training, change-management resources, and scalable architecture that can evolve with your growth.

“Above all, AI should enhance empathy, not erase it. The future of CX isn’t machine-driven – it’s human-led, AI-powered.”

How to Adopt AI Into Your Business

Bringing AI into your business might sound daunting, but with the right strategy, it can become your most powerful growth engine. Follow these steps when planning your AI implementation:

Define clear goals: Establish success metrics before deployment (e.g., CSAT, AHT, FCR). Track baselines and measure change over time.

Start with high-impact use cases: Pilot automation on frequent, low complexity tasks such as FAQs or routing. Quick wins build momentum and confidence.

Keep knowledge bases fresh: RAG and generative AI depend on accurate data. Outdated content undermines trust and increases hallucination risk.

Ensure seamless hand offs: Use unified desktops and orchestration tools so AI and human agents share context. Customers should never have to repeat information.

Invest in change management: Train staff to understand AI tools as allies. Address fears about automation replacing jobs and emphasise how AI enhances empathy and creativity.

Prioritise security and compliance: Choose vendors that meet GDPR and industry specific standards and ensure transparent handling of customer data.

Mapping AI Technologies to the Customer Journey

AI isn’t just transforming customer interactions – it’s reshaping the entire journey from first contact to long-term loyalty.

Here’s how key AI technologies align with each stage of the customer experience:

Onboarding

Chatbots and self-service portals guide registration and answer simple questions. Low code automation can integrate account creation with back-end systems.

Growth and Loyalty

Personalisation engines and predictive analytics identify upsell opportunities and churn risk, triggering timely outreach. Proactive, AI driven notifications build trust and loyalty.

Support and Recovery

Technologies such as agent-assist and sentiment analysis resolve complex issues quickly whilst generative and agentic AI bots provide accurate answers grounded in verified data.

Getting Real Results from AI & Automation

Technology adoption must translate into measurable business outcomes. The following metrics and practices help link AI investments to CX impact:

Performance Metrics

Customer Satisfaction (CSAT)/Net Promoter Score (NPS): AI enabled contact centres report CSAT improvements of around 37 percent and even revenue increases of 30 percent.

Average Handle Time (AHT)/First Contact Resolution (FCR): Automation slashes AHT by 12%, surfacing relevant information and routing tasks efficiently. Gartner projects that conversational AI in contact centres  will cut agent labour costs by $80 billion by 2026. Read our guide on reducing Average Handle Time using AI here.

Agent Retention and Productivity: Offloading repetitive tasks to AI boosts agent efficiency and reduces staff turnover. Studies show that generative AI assistants  increase agent productivity by 14 percent on average.

Operational Cost Reduction: Companies using generative AI report savings across the board. Automating a portion of support tickets can reduce costs per contact, while AI powered systems have led to jumps in customer satisfaction and increases in retention.

AI & Automation Trends for 2026

The future of AI and automation in customer experience (CX) is being shaped by five major trends that will redefine how businesses operate and engage with customers.

Agentic AI Systems

CX is shifting from reactive automation to autonomous orchestration, driven by agentic AI that can independently analyse data, make decisions, and execute customer-facing actions in real time. These AI systems no longer wait for human prompts – they proactively identify issues, coordinate across tools, and deliver outcomes without manual intervention.

By 2026, leaders will view AI not just as a digital assistant, but as a trusted operations partner capable of resolving complex service requests, personalising offers, and continuously optimising journeys at scale.

AI-Driven Orchestration Models

Rather than adding automation into legacy workflows, enterprises are re-architecting CX around AI as the operating system for decision-making and coordination. These orchestration models let AI route conversations, prioritise tickets, trigger fulfilment, and align marketing, sales, and support into one adaptive system.

 Ethical & Trust-Centred AI

As AI takes on more customer-facing responsibility, trust is becoming the currency of great CX. Brands must ensure algorithms are transparent, explainable, and free from bias, especially in service recovery, pricing, or claims processes. By 2026, organisations that prioritise AI will win customer confidence and protect long-term brand equity.

Human + AI Collaboration

Despite the rise of automation, the human role is CX becoming more strategic than ever. AI will handle scale, speed, and data-driven precision, while human agents focus on emotional intelligence, complex judgment, and creative problem-solving.

By 2026, hybrid teams – where humans supervise, train, and collaborate with AI systems – will define the gold standard of experience delivery, blending efficiency with empathy in every interaction.

AI Support with a Human Touch

Agent-assist platforms act as intelligent, real-time copilots, helping customer service teams work faster, think clearer, and connect more deeply. These systems free agents from repetitive tasks and cognitive overload, allowing them to focus on what they do best.

Real-Time Transcription and Analysis

Speech-to-text tools capture every nuance of a conversation while sentiment analysis detects emotion and intent. This immediate feedback loop helps agents adapt their tone, pacing, and strategy mid-conversation – turning reactive exchanges into proactive, empathetic service moments.

Knowledge Retrieval

Instead of searching through endless databases or documents, the AI surfaces the most relevant FAQs, product information, or policy references in real time. This instant access not only boosts accuracy and speed but also ensures customers receive consistent, up-to-date guidance.

Intelligent Responses and Next-Step Suggestions

AI-generated replies and recommended actions act as starting points that agents can review and personalize. This results in faster resolution times, a unified brand voice across customer communications, and more room for agents to bring their own judgment and warmth into every message.

What Agent-Assist Can do For Your Business

Agent assist is far from a fad – companies that deploy agent assist solutions are seeing measurable results. According to Microsoft research reviewing AI agents across sectors, organisations reported a 12% reduction in average handling time. Additionally, 10% of cases that typically required colleague collaboration were resolved independently with the help of virtual assistants. Together, these improvements drive lower costs, higher morale, and a better customer experience.

Your AI & Automation Journey

AI and automation are not about replacing people; they’re about amplifying human potential. When thoughtfully implemented, technologies like conversational AI, predictive analytics and low code orchestration enable personalisation at scale, proactive engagement and emotionally intelligent service.

To succeed:

1. Define clear goals and metrics.
2. Select technologies aligned with your CX strategy.
3. Keep data accurate and knowledge bases current.
4. Empower agents with AI rather than replacing them.

By following these principles, organisations can transform customer experience from reactive service into proactive, data driven relationships that deliver real business impact. The future of CX belongs to companies that embrace AI and automation in customer support while keeping the human at the centre of every interaction.

FAQs

How Does AI Improve Customer Experience?

AI enhances CX by personalising interactions, predicting needs and resolving issues faster. For example, AI enabled contact centres reduce average handling time by about 21 percent, boost agent efficiency by 20 percent and raise customer satisfaction by 37 percent.

What’s the Difference Between Generative and Agentic AI?

Generative and agentic AI each play distinct but complementary roles in transforming customer experience. Generative AI focuses on creating content based on learned patterns from data, allowing brands to deliver highly tailored, human-like interactions at scale. Agentic AI, on the other hand, takes this a step further by combining reasoning, decision-making, and autonomous action; it doesn’t just generate responses but proactively executes tasks across systems to resolve customer needs.

Will AI Replace Human Agents?

The recent wave of layoffs in customer experience and support roles suggests that automation is no longer just a theoretical threat – it’s already here. While humans remain part of the customer-service equation, the nature of their work is changing – the routine queries are increasingly being handled by machines, and human agents are being reserved for more complex, nuanced interactions.

How Should Organisations Begin Their AI Journey?

Start with a clear objective and a manageable scope. Pilot AI on high volume, low complexity tasks, measure results and iteratively expand. Maintain a clean knowledge base and choose technologies that integrate easily with your existing systems.

Is it Safe to Trust AI with Customer Data?

Yes – provided vendors demonstrate strong encryption, compliance with standards like GDPR and transparent data handling policies. Choose partners that prioritise security and explain how they use and store data.