The moment AI for contact centers became the backbone of enterprise service

AI for contact centers is moving from pilot projects to core enterprise systems. In the last month, big vendors and customers signaled a shift. Therefore, companies that touch customer experience — from banks to commerce teams — must pay attention. This post pulls together five recent developments to explain what is happening, why it matters, and what leaders should do next.

## Microsoft + Legal & General: AI for contact centers moves mainstream

Microsoft’s deal with UK insurer Legal & General shows AI for contact centers is no longer experimental. Legal & General will use Dynamics 365 Contact Center, integrated with Microsoft Copilot, to support service for 12.4 million customers. For example, agents will have AI assistance for faster answers and smoother handoffs. Additionally, the integration suggests enterprise contact centers are becoming platforms — not just phone systems.

This matters because insurance is a high-volume, high-trust industry. Therefore, the choice to embed Copilot signals confidence that AI can improve accuracy and speed without degrading trust. Moreover, because Dynamics 365 is part of a broader enterprise stack, the project highlights how contact-center automation is being tied directly to customer records, policy systems, and back-office workflows. Consequently, the line between customer service and the rest of the enterprise continues to blur.

Looking ahead, expect other regulated industries to follow. However, they will watch for compliance safeguards and measurable service improvements. For now, the L&G-Microsoft project is a clear example of AI for contact centers scaling in a real, customer-facing context. The impact will be both operational — faster resolution — and strategic — deeper data integration across the business.

Source: CX Today

Five9 and Europe’s CCaaS surge: what vendors and buyers should know

Europe’s contact center market is heating up. IDC’s MarketScape named Five9 a leader as the sector grows from $1.5 billion in 2024 to a projected $3.7 billion by 2029. Additionally, IDC projects roughly a 20 percent compound annual growth rate. Therefore, investments in cloud contact center software (CCaaS) and the AI features that come with it look set to accelerate.

For enterprises, the trend means more choice but also more complexity. Vendors like Five9 are competing on platform capabilities, AI tooling, and regional compliance. For example, stronger AI models and better integration options will be decisive selling points. However, buyers must weigh features against data residency, security, and the ability to integrate with in-house systems.

Furthermore, procurement teams should prepare different evaluation criteria. Consequently, success will depend on flexibility: can a CCaaS provider plug into existing CRMs, support conversational AI, and handle compliance needs? Meanwhile, platform maturity will matter less than the ability to deliver consistent, measurable outcomes like reduced handle time and improved first-call resolution.

In short, the European CCaaS boom signals a broader market shift. Therefore, organizations must move quickly to define use cases and pilots. Otherwise, they risk selecting platforms that look modern today but fail to integrate into their broader service ecosystems tomorrow.

Source: CX Today

Cisco + Salesforce: AI for contact centers meets CRM integration

Cisco’s Webex Contact Center for Salesforce is another sign that contact centers are becoming tightly woven into CRM systems. The new offering embeds voice and digital channels directly within Salesforce, using the Bring Your Own Channel (BYOC) pilot program. Therefore, agents and sales reps can work in one interface without switching tools.

This matters for daily operations. For example, having customer interaction history, case data, and AI-powered prompts available inside the CRM reduces friction. Additionally, tighter integration can improve handoffs between sales and service teams. Consequently, customer journeys become smoother when context flows effortlessly across touchpoints.

From a strategic view, the integration highlights a practical lesson: modern customer experience requires reducing tool fragmentation. However, this is not only a technical challenge. It is also an organizational one. Teams must align data definitions, privacy rules, and performance metrics. Meanwhile, IT leaders should favor partners and platforms that offer plug-and-play connectors to major CRMs.

Looking forward, expect more CCaaS vendors to prioritize CRM-first integrations. Therefore, enterprises should audit their CRM usage and identify the customer workflows that matter most. In doing so, they will be better positioned to pick contact center platforms that drive measurable improvements in customer experience.

Source: CX Today

Generative AI and B2B discovery: changing how buyers find vendors

A new study shows generative AI is altering vendor discovery in B2B markets. According to research from Responsive, one in four B2B buyers now use GenAI more often than traditional search engines when researching vendors. Therefore, vendor discovery is shifting from keyword-driven browsing to conversational, AI-assisted exploration.

This shift has practical consequences. For marketing and sales teams, it means content must be structured to support AI prompts and concise summaries. Additionally, because AI often synthesizes information into short narratives, firms that publish clear, authoritative content will be more likely to show up in GenAI-driven recommendations. Consequently, the role of product pages, case studies, and technical documentation becomes more strategic.

However, there are risks and opportunities. On the one hand, GenAI can surface vendors faster and provide tailored comparisons. On the other hand, it can also compress the buyer’s perspective into a single AI-generated viewpoint, which may obscure nuance. Therefore, vendors should focus on verifiable, high-quality content that AI tools can cite and draw from.

Finally, sales teams should reframe discovery. Rather than waiting for leads to arrive through search, they should monitor GenAI trends and prepare short, AI-friendly content that answers common buyer questions. In this way, organizations can remain visible and relevant as buying habits shift.

Source: Digital Commerce 360

Salsify and product data: AI for contact centers relies on cleaner product information

Salsify’s new AI tools — Angie and the Intelligence Suite — aim to automate product experience management. This development matters beyond e-commerce teams. Product data is what powers accurate customer conversations. Therefore, cleaner, AI-enriched product content helps contact centers, chatbots, and AI assistants deliver correct answers faster.

For example, an agent who sees normalized product specifications and localized descriptions can resolve a technical question without escalation. Additionally, automated tagging and categorization speed up search and recommendation features. Consequently, companies see fewer errors and a better customer experience across channels.

Moreover, connecting PXM improvements to conversational AI creates compounding benefits. Cleaner data improves AI responses, which then improves buyer confidence. However, the process requires governance. Teams must ensure the data feeding AI assistants is current, validated, and consistent across systems.

Looking ahead, expect product teams to work more closely with customer service. Therefore, investments in product data platforms and AI automation will have ripple effects across sales and support. In short, product content is now a strategic asset that powers AI for contact centers as much as it powers online shopping.

Source: Digital Commerce 360

Final Reflection: Connecting the dots for leaders

Taken together, these developments tell a clear story. First, AI for contact centers is maturing from stand-alone experiments to integrated enterprise systems. Microsoft and Cisco are building deep CRM and enterprise links. Meanwhile, Five9’s rise and market growth in Europe show platforms are becoming the default choice. Second, the way customers and buyers find vendors is changing as GenAI grows in importance. Therefore, content strategy and product data are becoming as crucial as telephony and routing. Finally, clean, governed data — from product catalogs to customer records — is the glue that makes AI useful and trustworthy.

For leaders, the implication is simple: prioritize integrations and data hygiene alongside AI features. Additionally, set measurable goals for customer outcomes, not just technology. With that approach, organizations can harness AI to reduce friction, speed service, and create more intelligent, consistent customer experiences across channels.