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.” 

To kick things off, there are six predictions that all examine what might be the most tangible shift taking shape in customer experience: agentic AI moving from underwhelming chatbots into systems that can actually handle real work.

After years of disappointing automation projects, the technology has reached a point where self-service might finally live up to its billing.

Meet the experts:

• Simon Thorpe, Director of Global Product Marketing for Customer Service & Sales Automation at Pegasystems
• Kishan Chetan, EVP and GM of Agentforce Service at Salesforce
• Matt Price, CEO of Crescendo
• Hakob Astabatsyan, Co-Founder & CEO of Synthflow AI
• Matthias Goehler, CTO in the Europe region for Zendesk
• Zeus Kerravala, Principal Analyst at ZK Research

The Chatbot Problem Nobody Wants to Talk About

Simon Thorpe, Director of Global Product Marketing for Customer Service & Sales Automation at Pegasystems, isn’t mincing words about where self-service has been.

“Look, everyone is talking about AI right now. And for good reason,” he says.

“But the thing that I’m really excited about is the fact that we can finally deliver self-service that actually works for our customers. You know, self-service that can get real work done. It’s able to resolve issues, complete tasks, deflect work from our centers and it’s self-service that our customers are actively going to want to use.”

Customers actively wanting to use self-service has been the unicorn of CX for the better part of two decades. Chatbots and IVRs promised a lot but mostly delivered frustration.

Simple queries? Sure. Anything remotely complicated? Straight back to the queue.

Thorpe sees agentic AI changing that dynamic because it can reason, adapt, and understand natural language in ways that rigid scripting never could.

He explains “What once took months is now going to take weeks, which is tremendously exciting.”

But there’s a catch. Speed without structure creates chaos, particularly in regulated industries where processes can’t just be improvised by an AI agent with good intentions.

“Without governance and workflow or workflow backbone, AI agents can go rogue. They can ignore processes. They can introduce risks.”

His solution is pairing agentic AI with enterprise-grade workflows that act as guardrails, ensuring “your rules, your regulations, your standards are consistently applied every single time.”

AI Agents Move from Pilot Projects to Production

Kishan Chetan, Salesforce’s EVP and GM of Agentforce Service, believes 2026 is when AI agents move away from experimentation toward becoming infrastructure.

“For me, the CX prediction for next year, the biggest one, is far more mainstream of AI agents,” he says.

“Companies across the board will use AI agents in their customer experience, and they’ll use that for different processes, and that’ll work seamlessly with their human service reps.”

The emphasis on working alongside humans rather than replacing them reflects how the conversation around AI has matured. Early hype suggested automation would eliminate jobs.

The reality is messier and more interesting: AI handles volume and repetition, humans manage complexity and judgment.

When AI Outperforms the Average Agent

Matt Price, CEO of Crescendo, makes a prediction that’s bound to spark debate: AI agents will become more empathetic and more efficient than humans in 2026.

“On average across all of the interactions between service agents and AI, AI will perform better because on average, AI assistants are able now to have great language, detect tone and respond appropriately to customers in the moment and have full access to all of the information that they need in order to give customers what they want, which is an answer.”

Price isn’t suggesting every AI interaction will beat every human one. Top-tier agents will still outperform AI. But AI doesn’t have bad days, doesn’t forget context, and doesn’t struggle with tone on the 200th repetitive call of the day. That consistency matters.

There’s also a perception angle here, as Price notes that “a lot of the time for clients, it’s not necessarily just how well you serve them, but how much effort you put in.

“And there’s nothing better than showing the amount of effort that’s been put in, than putting a human in the loop rather than an AI agent.”

So even as AI gains emotional intelligence, there will still be moments where customers want to know a person is involved.

The Innovation Slowdown (That’s Actually Good News)

Hakob Astabatsyan, Co-Founder & CEO at Synthflow AI, predicts 2026 will see a decline in forward-looking innovation and instead focus on making AI work at scale.

“My prediction for 2026 is that we will be seeing less groundbreaking innovation that we have experienced in the last two years and more ROE and value delivery to the customers, to enterprises.

“What I mean by that is more scalable, more reliable platforms that allow the enterprises to go into production and deploy agents, voice agents, but also chat, omnichannel chat and text agents into production and scale them to millions of calls.”

That might sound boring compared to the breathless pace of the last couple of years, but it’s what enterprises actually need. Over-the-top innovations don’t matter if the technology can’t handle production traffic without breaking.

From Reactive to Proactive

Matthias Goehler, CTO in the Europe region for Zendesk, sees AI shifting from solving problems to preventing them before customers even notice.

“My biggest prediction for 26 when it comes to CX is that AI will move from automation to anticipation,” he says. “Instant resolution still remains the biggest expectation of customers. But on top of that, customers also more and more expect personalized engagement.

“And then even on top of that, if companies could start to become more proactive and reach out to customers instead of customers having always to reach out to companies, I think then we’re really talking about the gold standard in service.”

That’s a higher bar than most organizations have reached, but the technology to get there has begun its early stages.

Customers Will Actually Prefer Virtual Agents (For Simple Tasks)

Zeus Kerravala, Principal Analyst at ZK Research, predicts that for straightforward requests, customers will start choosing virtual agents over humans.

“My CX prediction for 2026 is that virtual agents get so good that for simple requests, people start to prefer the virtual agent over humans,” he says.

“And you might think that this is contrary to everything we believe, but if you look back at the early days of online banking and restaurant reservations online, people said that back then that no one would prefer a computer over a person. And in both cases that certainly wasn’t true.”

Kerravala draws a parallel to other initiatives that originally faced skepticism but eventually became preferred options once they proved faster and more reliable.

“Virtual agents can do things faster and more accurately than people now for complicated tasks. We’re still going to do prefer to a human, but in 2026 the quality of virtual agents will get so good that for simple tasks we’re going to prefer machines over people.”

The prediction doesn’t suggest humans become obsolete. It suggests customer preferences will align with the strengths of each channel.

What This Means for 2026

The common thread across these predictions is straightforward: AI agents are maturing from disappointing novelties into reliable tools that can handle real customer service work.

Self-service that actually works, agents that operate alongside humans without replacing them, and systems that anticipate problems rather than just reacting to them.

These aren’t abstract possibilities anymore. They’re becoming baseline expectations.

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.” 

The cloud communications vendor revealed that it had taken significant measures to strengthen its service governance. 

This strategy will allow the company to expand its range of security and compliance frameworks, establishing itself as a trustworthy provider for customer enterprises. 

The implementation, better known as ISO/IEC 27018, is a well-established privacy standard used by enterprises worldwide to protect customer data in public cloud environments. 

And with security concerns now at an all-time high, vendors will need to consider how best to protect their customers’ data. 

Darren Remblence, Chief Information Security Officer at 8×8, highlighted how customer demand for security around data management is a bare minimum requirement. 

“Customers should never have to trade speed or innovation for security,” he explained.

“ISO/IEC 27018 gives organizations even stronger guarantees that their data is handled responsibly and transparently.  

“It means they can move faster, meet compliance requirements with confidence, and trust that privacy is built into every part of their communications experience.”

This privacy standard is a code of practice that protects personal data from public cloud providers and shields any private or personally identifiable information (PII) from falling into the hands of third parties. 

It contains core regulations for enterprises that choose to adopt this standard, such as data processing with customer consent, supporting customer data handling, transparency with data protection approaches, and implement strong security measures, including restrictions and encryption methods. 

This standard also includes controls for handling data access, use, transparency, and dealing with incident response. 

This assures customers that 8×8 is meeting the higher standards required for durable data handling. 

What This Means For 8×8 Customers

This implementation into 8×8’s security management system enhances privacy and security for 8×8 Platform for CX, a unified CX communications platform that includes multiple capabilities for customer-facing teams and customer interaction management. 

Customer enterprises can enhance their vendor onboarding routines with faster security evaluation, reduced data exposure risk, and transparency with data handling. 

It also enables 8×8 customers to feel secure in where they place their data, with constant review and improvement from the vendor’s security and compliance team to ensure these standards are kept, including privacy practices, data handling, and cloud architecture. 

And with the customer playing a significant role in its activity, data processing can only happen under customer instruction and is kept informed consistently about its storage whereabouts and who can access it. 

This highlights 8×8’s commitment to its customers’ privacy and security, assuring that data handling is less likely to be compromised or misused. 

Growing 8×8’s Security Portfolio

The privacy standard also allows 8×8 the chance to build up its security and compliance portfolio to meet the growing demands from customer expectations. 

This portfolio has also included similar frameworks, including ISO/IEC 27001, ISO/IEC 27017, SOC 2, and HIPAA mapping, which involve building and assuring security controls and management within a system, as well as several other regulatory standards to assure 8×8’s commitment to security requirements. 

This decision also comes during a time when customer expectations have risen significantly in the last year, after a wave of cyberattacks that profoundly impacted the customer experience sector, including CX giants such as Salesforce, Zendesk, and Google. 

This places risk on data handling processes such as migration and storage methods, forcing vendors like 8×8 to stay ahead of cyberattack activities. 

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 

This comes after its annual report revealed that AI implementation had increased by 282% since 2024. 

These tools enable enterprises to deploy AI agents without worrying about the reliability and safety of their performance within a system. 

Salesforce’s observability tools provide AI agents with the capabilities to analyze performance, optimize interactions, and monetize stability. 

Agent Analytics

This capability allows enterprises to view how well an AI agent is operating through monitoring its movements, how it’s improving/declining, and where these pain points are coming from. 

This can be turned into performance data, trends, and insights to understand how efficiently these agents are performing and take actionable steps to improve their usage. 

This can also be done across all implemented agents, allowing enterprises to view their agents’ overall effectiveness on customer interaction and support their continuous improvement. 

Agent Optimization

As a key observable capability, Optimization offers customer enterprises full transparency with each agent interaction. 

Customers can uncover how agents make decisions and what led them to make those choices, highlighting performance gaps and session flows to diagnose any issues and deduce the steps needed to improve its performance. 

This can include prompt, rule, or data source adjustments to solve misinterpreted information, inconsistent results or agent hesitation. 

Salesforce provides access to end-to-end visibility for customers to view each agent’s response and action, even with larger, complicated action chains. 

For less varied issues, similar requests can be accumulated to uncover larger problems in patterns or trends. 

Customers can also identify an agent’s configuration issues to pinpoint how an agent’s behaviour is affecting its operation and uncover which areas need to be retrained or personalized further for improved performance. 

Agent Health Monitoring 

This capability can monitor an AI agent’s reliability and safety level to ensure that it is running as expected. 

It provides almost real-time visibility and alerts when the agent is performing unpredictably, notifying the company before any significant damage takes hold. 

It measures an agent’s ability to handle requests, time taken to respond, and tracks incidents such as failures, breaks in activity, or invalid responses. 

By leveraging the capability, teams can speedily detect and resolve issues to minimize agent downtime and continue productivity. 

This tool is formed by two of Agentforce’s components, acting as the foundation for the observability tool by supplying the data and governance structure needed to monitor agents: 

• Session Tracing Data Model: By logging every agent interaction, the data model can store all its data in Data 360 and provide the observability tool the means to generate reliable analytics, error identifiers, and support optimization for unified visibility.
• MuleSoft Agent Fabric: This enables enterprises to control, register, and review agents to justify how they function and interact. 

AI Implementation Report 

In a report published in November, Salesforce announced that AI implementations had increased to 282% since last year. 

This data reveals that companies are now at a far better position to deploy pilot projects at scale rather than risk the threat of experimentation. 

Despite this, data governance, security, and trust remain high priorities, requiring risk management across workflows. 

This means that more companies are going to require higher visibility and control across large-scale AI deployments, which is where Salesforce’s observability tools come in. 

By supporting enterprises with agent interactions, Salesforce’s observability tools can decrease operational risk by allowing teams to keep up to date with agent visibility and analytics to keep agent deployments stable. 

Reddit, a customer of Salesforce, highlighted how Salesforce has allowed the customer enterprise to scale agents securely through consistent visibility. 

John Thompson, VP of Sales Strategy and Operations at Reddit, stated: “By observing every Agentforce interaction, we can understand exactly how our AI navigates advertisers through even the most complex tools.  

“This insight helps us understand not just whether issues are resolved, but how decisions are made along the way. 

“Observability gives us the confidence to scale these agents, continuously monitor performance, and make improvements as we learn from their interactions.”

At the Call and Contact Centre Expo 2025, the primary focus of many sessions was centered around AI, trends, and how to join the never-ending CX competition.

Fola Olafare, Senior Contact Center Delivery Manager at Transport for London, highlighted TFL’s approach to differentiate from the mainstream AI-focused contact space toward a more customer-centric one.

The event, ‘Mind The Gap: How TFL’s CX Strategy is Transforming Customer Experience’, emphasized how organizations can still function in the modern day meaningfully without turning straight to AI for results.

Olafare highlighted what he sees as the current CX trend issue:

“You’ll just see AI laced everywhere – it’s getting to the point of bringing AI for the sake of bringing AI.”

Less AI, More Human

However, with customer loyalty being a valuable currency in the CX space, the customer-centric trend has allowed TFL to thrive, having simplified their customer service approach drastically in the last decade.

By focusing less on AI integration, customer service can continue the traditional approach to drive meaningful human experiences to each individual customer.

He highlighted TFL’s current “Core ethos about listening to our customers and demonstrating that we care.”

Previously, TFL saw frequent barriers between company and customer.

“From a customer point of view it wasn’t great, we had 15 different phone numbers and 35 different emails.

“Maybe 1o, 12 years ago we didn’t have that influence.”

Today, customer’s transportation experiences are leaps and bounds ahead.

He said, “From a contact center point of view, we’ve come a long way representationally,”

“We have a really nuanced support for our visitors – allowing us to provide a dedicated care service for all our customers,

“Telephone is a great starting ground for us – now we have one phone number for customers.”

Customer’s can go to customer support to receive advice on travel planning, how to handle complaints, and discuss transportation issues within their area.

This has also included showing support for customers after negative or traumatizing transportation experiences.

“The aftercare support to the victims of life changing incidents that happen on our networks – providing them that support for a good duration.”

This approach has shown in its results, with 2024 seeing 30 million daily journeys, 9,000 buses, and over 1,400 e bikes around the city, whilst also managing 25% of London’s roads, improving overall transportation for residents and visitors.

In fact, this has prompted the London mayor to set a goal to see more people using public transport, hoping that “by 2041, 80% of customer journeys are being taken by customer transport.”

Automation is Still Key

Despite the focus on human experiences, automation continues to play a role in TFL’s customer experience, utilizing that tool through analyzing real customer experiences to provide its customer’s with a system they actually need.

He said, “We do some much from an automation point of view – we have a lot of strong algorithms working in the background to work out different anomalies.

“We’ve now ensured that intention is available for customers from a journey point of view by enhancing them with our alternative journey messages.” 

And whilst TFL does implement automation in the organization, it recognizes that setbacks will occur with this tool.

“For every automated journey we have, we acknowledge it may not work as well.”

However, in return, “You can have really great conversations for resolving that issue in a really caring way.”

Despite this approach, TFL are conscious about keeping up with customer demands and circumstances.

“We also want to make sure we’re adapting to customer circumstances, to have a really good strong set of customer values – we want to be open and transparent about what we’re doing.

“From a TFL point of view, what excited me is there is so much opportunity to make a lot of people’s lives better in an integrated way.”

At London’s annual Call and Contact Centre Expo, the telecommunications company revealed how its customer-centric approach to limit consumer frustration has improved its overall loyalty.  

This solution is aligned with Vodafone’s strategy to transform customer experience. 

Customer experience results have been improved since the strategy launch in July 2025, with 9 out of 15 of its markets leading with this new strategy, resulting in a six percent reduction in company detraction after the first few months. 

When first researching customer experience strategies, Vodafone discovered that seamless interactions were a high priority for customers, with frequent causes of company detraction relating to negative customer experiences. 

These incidences included: holding for additional agents, transferring calls, repeated conversations, and a company’s failure to keep promises. 

In fact, they had discovered that customers who had experienced at least one bad experience from customer service were 4 times more likely to abandon the company. 

Melda Sofuoglu, Global Senior CX and Service Excellence Senior Manager at Vodafone, explained how the customer expectations have grown since the rise of AI in the CX space:

“We are operating in a rapidly changing industry – expectations have grown to 24/7 service.” 

However, research revealed that as long as customer interactions remained seamless, then customers would be more likely to remain with a company that avoided friction. 

And when companies failed to deliver on results, 46% of customers would research Google to find answers to their issues, driving enterprise intensity to produce better results as customers discover what sets the bar in the CX space. 

Just Ask Once

Vodafone has since researched some of the leading customer services spaces online, including Google and Octopus, to take elements and utilize the most productive strategy for resolving customer complaints. 

The strategy, known as ‘Just Ask Once’, began in 2024 to target pain points in the company’s Albania market, with the aim of resolving a customer issue after just one interaction. 

This strategy utilized generative AI omnichannel service to avoid customers re-explaining issues and call waiting times to resolve queries, whilst also keeping customers in the loop if issues cannot be solved immediately to avoid confusion or miscommunication via text. 

This is also done by deploying Vodafone’s suite of capabilities, such as Super-TOBi, a generative AI assistant that handles complex conversations and queries in comparison to the standatd TOBi chat bot. 

This strategy, however, is not designed to elminate human agents from the mix, but rather to place them at the center of this strategy with chat bots as a second option during traffic spikes, with many of these queries being completed through human agents rather than bots to avoid frustration. 

These bots simply allow agents to complete Vodafone’s vision for setting the new standard for customer experience centered around meaningful interactions and added loyalty, even when mistakes occur. 

This has involved significant investments in human agent training to keep them adapted and involved in the consistently changing state of customer experience, rather than eliminating their positions for AI-only service. 

However, Vodafone has experienced setbacks in this strategy amongst social media responses. 

Aimie Jago, Global Senior CX and Service Excellence Senior Manager at Vodafone, explained how the company are managing the influx from social media:

“In some markets we see some backlash on social media – its more about previous customer experience through chat bots.” 

Resolving past customer interactions remains challenging for Vodafone, arguing that to tackle this previous frustration into returned loyalty they need to experience this new transformation. 

This has affected the company’s ROI after significant investments; however, they are expecting to receive this once business case justification takes place. 

Furthermore, Vodafone’s continues to remain vulnerable, as this strategy depends primarily on technology, investment, and strong sponsorship, due to its small space within the CX space.  

Today, this strategy is being implemented by Vodafone’s global markets, aiming to champion the voice of the customer by creating a strong customer community, available to customers through the Vodafone app. 

At Microsoft Ignite 2025, the tech giant announced its plans to transform how it implements AI and how to improve general productivity. 

Microsoft has offered various AI agents for specific systems and companies for personalized success. 

Microsoft Copilot 365 

Within Office 365, Copilot acts as an assistant to support teams in preparing and managing their communications smoothly, working separately across each application to reduce overall preparation times. 

In Outlook, Copilot can organize a user’s inbox from high volumes of emails to summarized and highlighted information that needs immediate attention, as well as gather any information relevant to the user’s current task for quick response times and correct information gathered. 

In Word, customers can utilize Copilot’s assistance with drafting and refining content, providing summarized notes of material, and lengthening notes into documents, allowing teams to prepare for meetings and reports with limited information. 

In PowerPoint, users can create highly efficient presentations through Copilot’s capabilities to develop slides, draft content, and reposition information to fit their audience’s needs, allowing for clearer presentations with effective outcomes. 

In Excel, Copilot can break down data information through summaries and identify common trends within the spreadsheet, allowing for quick turnarounds in analysis explanations for other customers or employees. 

Copilot Studio

Within Copilot studio, teams can design personalized agents to fit their needs to work inside Microsoft 365. 

This tool can be used support connections between Microsoft’s own content as well as external systems through APIs, meaning customers can utilize the agent outside of Microsoft’s products for quicker results. 

It offers natural language when advising users on tasks, queries, or support with internal workflows and repeatable tasks, minimizing the need for human agent automation. 

For additional security, Copilot studio allows users to manage their custom agents to reassign roles to fit company policies, permissions, and security maintenance, obtaining an Entra Agent ID to verify an agent to operate under secure governance. 

Copilot Mode with Edge 

Copilot Mode can now be used on Microsoft Edge to analyze open tabs to summarize content and research within a browser. 

This reduces time spent tab switching and helps users stay on task by feeding them the relevant information. 

Information can be obtained from articles, texts, and videos, summarizing key points and explanations by interpreting knowledge from different sources at the same time, which can be useful for reviewing widespread customer experiences of products or services. 

Copilot Mode is only entitled to utilize information the user gives it access to, allowing the tool to work within company guidelines and provides the user with the relevant information it receives. 

Agent 365 – provides security and governance for copilot (link back to previous article) (100) 

Working as Copilot’s governance layer, Agent 365 provides organizations with the ability to control AI agents and how they interact within the business. 

Agent 365 utilizes Entra ID to identify each agent within an ecosystem and aligns it with company policies, allowing organizations to set limits and permissions when needed to stop agents from working outside company expectations. 

These tools also allow companies to track AI activity to apply compliance rules to avoid data loss on behalf of the agent, allowing organizations to maintain control while the AI agents continue to complete their tasks.  

Copilot Business 

Working as a slightly different version of Microsoft 365 Copilot, Copilot Business is designed to support small to mid-sized organizations using AI tools. 

Similarly to the 365 Copilot tool, this feature allows businesses to summarize their material, advise on email management, and create presentations using the provided Microsoft 365 apps to reduce time spent on administrative tasks. 

This tool, however, does not require a complex setup as the needs required for SMB don’t necessarily demand the amount of compliance and data needs to function. 

Copilot Business can but used to work at a basic level, whilst continuing to provide analysis and reports of data and communications to increase productivity within smaller businesses. 

Microsoft Ignite 2025 

Microsoft Ignite will run from Tuesday 18th November to Friday 21st November in San Francisco. 

The company has emphasized its commitment to agentic AI and is set to showcase this message throughout the conference, as well as further touch on issues such as Security and Governance, and Identity and Access.