In its third-quarter earnings call, the software company announced that its total number of customers had increased to almost 300,000.

These tactics reveal how enterprises are willing to adopt AI with the correct tools given.

HubSpot CEO Yamini Rangan, remains confident in HubSpot’s continuing strategy to improve its customer tool adoption and outreach. 

She said: “We are uncovering new ways to drive efficiency and finding signals to show our customers what’s possible with AI.  

“I’m more confident than ever in our strategy and our ability to deliver value for customers in this new era.”

Rangan recognised that the result of this was down to three different factors: 

1. Multi-hub adoption
2. Answer Engine Optimization strategy
3. Platform consolidation

Multi-Hub Adoption  

HubSpot has adopted the multi-hub strategy to encourage consumers to involve their enterprises in more than one hub. 

This solution addresses the current trending issue of tool fatigue by supporting its enterprise customers to meet these AI innovations head-on. 

In fact, this has become the model standard for a large number of customers, with 43% of customers who subscribe to HubSpot’s Pro Plus also subscribing to all three primary hubs. 

Along with this strategy, the company has continued to enhance its agents across the board, as well as launching a new data agent towards the end of the quarter. 

This approach has seen higher results and activity across all hubs and agents. 

In one example, customers who used the Marketing Hub saw improvements in results and click-through rates thanks to its embedded AI features, such as the AI-powered email. 

Its Prospecting agent saw a total of 6,400 customers during the quarter, with an increase rate of 94% and high rates of engagement with over 1,000,000 recipients. 

Data agent, which launched recently at INBOUND in September, has already collected 700 customers. 

HubSpot’s digital assistant ‘Brief’ has more than doubled in weekly usage for record summarizing and finding performance engagement insights. 

Its Data Hub can be beneficial to this process, by helping customers to unify data from across an enterprise into one location. 

Along with its standardized bots, HubSpot has also introduced its Breeze studio, allowing customers to create and design their own agents to fit their enterprise’s needs. 

AEO

HubSpot’s Content Hub has also launched its Answer Engine Optimization (AEO) strategy to improve its customers’ visibility online and in AI-generated answers, allowing them to measure and refine their tactics. 

This has included the launch of its AEO-focused tool, such as the Loop, a clear guide for how companies can drive traffic growth from both human and machine intelligence. 

The tool has received strong responses from customers, with a total of 270 million viewers and 100,000 on the Playbook experience. 

HubSpot’s Data and Marketing hubs have also been beneficial to the launch of Loop, helping to create personalized customer profiles and content targeted towards buyer objectives. 

The second AEO product launch was the AEO Grader, which allows companies to grasp their popularity levels and image when they’re searched on AI engines. 

Platform Consolidation

From strong results in the third quarter, HubSpot has seen substantial benefits for its customers from its unified, platform-first customer solution. 

A primary justification for this upwind in the platform’s customer growth is its cost-efficiency method, with more companies choosing to go for unified operations to avoid integration expenses, as well as to view their marketing, sales, and customer services all in one place to simplify their AI innovation process. 

This result has also benefited from HubSpot’s LLM connector approach, allowing its platform to connect with large-language-model (LLM) providers, such as ChatGPT and Gemini. 

This approach has seen an upsurge in consumer reach across its LLM providers, with ChatGPT reporting more than 47,000 customers activating its connector, with over half of them being Pro Plus users. 

Its cloud connector has also seen high levels of traffic, having been accessed by over 6,000 users. 

HubSpot refers to this approach as a “key part of [its] AI strategy”, with the LLMs using public available data to create the insights, HubSpot can offer context to the insights and make them ready for market teams to use. 

The company have also shown great success in its CRM, becoming the first to connect with all three – ChatGPT, Quad, and Gemini – for successful customer outcomes. 

HubSpot also outlined the success of its shift towards a universal usage-based pricing model during the quarter, set to extend across the entire platform. 

The system focuses on its AI agents’ actions, data hub syncs, and automation all under one operational framework. 

To track and monitor customer usage, HubSpot uses credits to measure customer value growth and their use of AI and data inside the system. 

By using more HubSpot tools, AI features, and data capabilities, customers can scale their value effectively without having to change their system environment. 

Rangan said:

“Our vision is to make the core seat essential with AI and data value for every go-to-market employee. Credits are another powerful emerging lever.” 

Key Q3 Financial Results

• HubSpot has revealed a global customer base increase of nearly 297,000, its total number of customers had increased by 10,900 
• Its total revenue saw a strong increase at $810MN, up by 18.4% year-over-year 
• The percentage of customer revenue retained above 80%, with customer net revenue retention at 103%
• Subscription revenue went up at almost $792MN, up 21% on an as-reported basis compared to Q3 2024 
• Other professional services and revenue had risen to almost $18MN, up by 19% on an as-reported basis compared to Q3 2024 

The move starts with Etsy sellers, with Shopify merchants such as Glossier, SKIMS, and Spanx due to follow.

According to OpenAI, the feature currently supports single-item purchases but will expand to multi-item carts and new regions in the coming months.

The system is powered by the open-sourced ‘Agentic Commerce Protocol’, co-developed with Stripe, which enables AI agents, people, and businesses to complete purchases securely.

Stripe users can enable it with minimal code changes, while others can connect through Stripe’s ‘Shared Payment Token API’ or by adopting the ‘Delegated Payments’ specification.

Merchant Control and Customer Experience

In practice, shoppers can move from product discovery to purchase without leaving the chat.

Recommendations appear organically, based on relevance rather than sponsored placement, with buyers able to confirm payment and shipping details directly in the interface.

Merchants remain the merchant of record — handling payments, fulfillment, returns, and customer support using their existing systems.

OpenAI said that while merchants pay a small fee on completed purchases, customer prices are unaffected.

The Strategic Implications

For enterprises, the development is about more than convenience. It reflects how ChatGPT is consolidating the buyer journey, taking on a dual role as both search engine and storefront.

This is part of a broader industry trend toward machine customers — AI agents that can act and transact on behalf of humans.

Gartner recently forecast that half of CEOs already have, or plan to develop, a strategy for machine customers.

CX Today has also reported on Google’s experiments with machine-to-machine customer service, which analysts described as an early indicator of this shift.

Questions for CX Leaders

The announcement raises key questions for customer experience leaders. If AI platforms such as ChatGPT mediate the entire buyer journey, how do brands maintain control over customer relationships and loyalty? What guardrails will be needed to ensure AI agents make authorised, transparent decisions? And how should channel strategies evolve if significant volumes of traffic and sales are redirected through third-party platforms rather than direct e-commerce sites?

Early Days, Bigger Picture

OpenAI has described Instant Checkout as a first step, with more functionality planned.

While the technical integration may be straightforward — particularly for merchants already using Stripe — the strategic consequences could be far-reaching.

Agentic commerce is no longer a distant prospect. With ChatGPT handling both discovery and purchase, the customer journey is changing shape, and enterprises will need to decide whether to embrace, adapt, or resist a future where AI agents play a central role in commerce. Assuming consumers take it up, that is.

Microsoft Steps Toward “Fully Autonomous Contact Centers” with a New-Look AI Agent

Microsoft has announced its new-look Customer Intent Agent in a move it describes as “accelerating the journey toward fully autonomous contact centers.”

The tech giant first unveiled the Customer Intent Agent, available across its Dynamics 365 Contact Center and Customer Service offerings, in January 2025.

Upon the original announcement, Microsoft showcased how the AI Agent scans service conversations to pinpoint the contact center’s core demand drivers, or ‘intents’.

From there, it clusters transcripts, case notes, and summaries to map each intent and outline the steps to a successful resolution.

That intelligence then plugs into other AI agents, automating knowledge article creation, informing self-service interactions, and boosting the agent-facing Copilot.

Meanwhile, the Customer Intent Agent keeps working in the background, unpacking emerging customer intents, enabling the creation of new knowledge content, and expanding the scope for contact automation (Read more…).

Salesforce Makes Changes to Its Agentforce Pricing Model (Again!)

Salesforce is continuing to tinker with Agentforce’s pricing model.

The goal remains the same: to reduce barriers to entry and get more of its 150,000+ customers on the AI agent platform.

As of May 2025, 8,000 of those customers are currently leveraging Agentforce.

Hoping to boost those numbers, Salesforce’s latest move is to introduce ‘pay-as-you-go’ and ‘pre-commit’ payment options.

Along with the pre-existing ‘pre-purchase’ option, Salesforce now offers three distinct ways to pay for Agentforce.

When sharing the new payment options, Bill Patterson, EVP of Corporate Strategy at Salesforce, underlined how they pave a path for “businesses of all sizes” to start testing and deploying AI agents. He said:

We’re removing the friction and lowering the barrier to entry so every company, whether they’re a long-time customer or trying Salesforce for the first time, can get started and see immediate value from digital labor with Agentforce.

The updates follow the introduction of that ‘pre-purchase’, consumption-based pricing model earlier this year (Read more…).

Lenovo’s Customer Service AI Chatbot Got Tricked Into Revealing Sensitive Information. Here’s How

Lenovo is the latest high-profile brand to have a security flaw exposed in its AI customer service chatbot.

Indeed, Security Researchers at Cybernews opened up Lenovo’s ChatGPT-powered customer service assistant, Lena, with jaw-dropping results.

Its investigation found that Lena can be tricked into providing sensitive company information and data.

Cybernews researchers were able to uncover a flaw that allowed them to hijack live session cookies from customer support agents.

With a stolen support agent cookie, an attacker could slip into the support system without any login details, access live chats, and potentially dig through past conversations and data.

And all it took was a single, 400-character prompt.

In discussing the investigation, the Cybernews researchers highlighted the relative ease with which AI chatbots can be duped:

Everyone knows chatbots hallucinate and can be tricked by prompt injections. This isn’t new. What’s truly surprising is that Lenovo, despite being aware of these flaws, did not protect itself from potentially malicious user manipulations and chatbot outputs.

The news comes soon after CX Today reported on how a different team of researchers cracked open a replica of McKinsey & Co.’s customer service bot, getting it to spit out entire CRM records (Read more…).

Zoom Expands the Scope of AI in Customer Service with a New Virtual Agent Use Case

Zoom has integrated its Virtual Agent with Zoom Phone, helping businesses connect callers directly with the department that can solve their issue.

Often, queries flow through to the contact center, where an agent either transfers the customer or plays the go-between.

However, thanks to this new capability, Zoom customers can unlock a new “24/7 AI receptionist”. That receptionist routes the customer to the best-placed department on the agent’s behalf.

Critically, it also interacts with customers, gauges their intents, processes inputs, and uses that intelligence to offramp the customer.

In “processing inputs”, the Zoom Virtual Agent (ZVA) takes helpful information from the customer and passes it to the employee, boosting their troubleshooting process.

Additionally, departments using Zoom Phone can utilize the Virtual Agent to automate tasks, such as booking appointments and providing customer updates. No longer are these capabilities limited to the contact center; they’re democratized (Read more…).

Indeed, Security Researchers at Cybernews opened up Lenovo’s ChatGPT-powered customer service assistant, Lena, with jaw-dropping results.

Its investigation found that Lena can be tricked into providing sensitive company information and data.

Cybernews researchers were able to uncover a flaw that allowed them to hijack live session cookies from customer support agents.

With a stolen support agent cookie, an attacker could slip into the support system without any login details, access live chats, and potentially dig through past conversations and data.

And all it took was a single, 400-character prompt.

In discussing the investigation, the Cybernews researchers highlighted the relative ease with which AI chatbots can be duped:

Everyone knows chatbots hallucinate and can be tricked by prompt injections. This isn’t new.

“What’s truly surprising is that Lenovo, despite being aware of these flaws, did not protect itself from potentially malicious user manipulations and chatbot outputs.”

The news comes soon after CX Today reported on how a different team of researchers cracked open a replica of McKinsey & Co.’s customer service bot, getting it to spit out entire CRM records.

Unpacking the Flaw

First of all, it should be noted that while Cybernews did uncover a flaw in Lenovo’s system, there is nothing to suggest that bad actors have accessed any customer data or information.

Cybernews reported the flaw to Lenovo, which confirmed the issue and moved quickly to secure its systems.

But how exactly were the Cybernews researchers able to dupe Lena?

The researchers have revealed that the prompt used contained the following four key elements:

• Innocent opener: The attack begins with a straightforward product query, like asking for the specs of a Lenovo IdeaPad.
• Hidden format switch: The prompt then nudges the bot into answering in HTML (alongside JSON and plain text), a format the server is primed to act on.
• The payload: Buried in the HTML is a bogus image link that, when it fails to load, pushes the browser to contact an attacker’s server and leak session cookies.
• The push: To seal it, the prompt insists the bot must show the image, framing it as vital to the user’s decision-making.

Worryingly, Zenity revealed earlier this month that 3,500 public-facing agents remain open to similar prompt injection attacks.

How to Prevent Your Chatbot from Becoming a Liability

Lenovo’s Lena case is a wake-up call for any company leaning on AI for customer support.

The core problem isn’t just a single flawed implementation; chatbots, by design, are eager to please. And when that eagerness meets poorly vetted inputs, things can go sideways fast.

Indeed, Lenovo is far from the first major organization to experience chatbot troubles.

The challenges aren’t limited to security flaws. AI chatbots have a long history of hallucinating and/or giving wrong or misleading advice.

Take New York City’s “MyCity” small-business assistant as an example. In April 2024, it misrepresented city policies and even suggested illegal actions to users.

Similarly, Air Canada recently found itself in court over its chatbot’s inaccurate guidance, with judges ruling the airline had to honor advice that was plain wrong.

Other errors have verged on the absurd. For instance, DPD’s GenAI chatbot was coaxed into swearing and composing a self-deprecating poem about the company.

These incidents underline just how unreliable chatbots can be.

For businesses, the question isn’t if an AI will make mistakes; it’s how prepared you are to contain them when they do make a mistake.

While the ever-evolving nature of AI-powered technology makes it impossible to put together a definitive guide on how businesses can prevent chatbot errors, the following steps will go a long way towards shoring up your defenses:

• Harden input and output checks: Never trust what comes in or goes out. Sanitize all user inputs and chatbot responses, and block execution of unverified code. It’s a simple step that could have prevented the session-cookie flaw in Lena.
• Verify AI outputs before acting on them: Web servers shouldn’t automatically treat chatbot outputs as actionable instructions. As is evident, blind trust can open the door to attacks.
• Limit session privileges: Not every bot interaction needs full agent-level access. Segregating privileges reduces the impact if a token or cookie is compromised.
• Monitor for anomalies: Keep an eye on unusual access patterns or unexpected requests. Early detection is often the only thing stopping small flaws from becoming major breaches.
• Test aggressively and continuously: Regularly simulate prompt-injection attacks or other AI-specific exploits. Proactive testing beats reactive firefighting every time.

Ultimately, while chatbots can boost efficiency and CX, they can only truly be relied upon if businesses pair them with strong security hygiene.

As all of the above examples have demonstrated, even big brands can overlook the basics – and in the world of AI, small oversights can escalate fast.

Often, queries flow through to the contact center, where an agent either transfers the customer or plays the go-between.

However, thanks to this new capability, Zoom customers can unlock a new “24/7 AI receptionist”. That receptionist routes the customer to the best-placed department on the agent’s behalf.

Critically, it also interacts with customers, gauges their intents, processes inputs, and uses that intelligence to offramp the customer.

In “processing inputs”, the Zoom Virtual Agent (ZVA) takes helpful information from the customer and passes it to the employee, boosting their troubleshooting process.

Additionally, departments using Zoom Phone can utilize the Virtual Agent to automate tasks, such as booking appointments and providing customer updates. No longer are these capabilities limited to the contact center; they’re democratized.

Celebrating the announcement, Smita Hashim, Chief Product Officer at Zoom, said: “When someone calls your business, it should feel easy and personal from the first hello. By combining AI that can listen, understand, and take action with the reach of Zoom Phone, our concierge virtual agent provides seamless and personalized support to all callers.

Whether a customer is calling to schedule an appointment, check an order status, or check product availability, Zoom’s concierge is available 24×7 and can deliver answers instantly, escalating to live employees only when needed.

In releasing this innovation, Zoom exploits the benefits of serving customers on one unified platform that includes CCaaS, UCaaS, and conversational AI solutions.

Few can offer such capabilities, which will particularly benefit businesses that don’t have big centralized contact centers, but smaller, scattered, and informal service operations.

Think of healthcare, for instance. The ZVA can take calls from a single number and route contacts, with context, to their closest GP’s office. Also, medical practitioners can leverage the AI receptionist to schedule appointments on the voice channel.

Also, consider a sector such as education. Many universities have dispersed helpdesks covering medical, hospitality, and other functions. The ZVA can route interactions between locations, collecting context and enabling a centralized support function.

That said, the ZVA can also act as a concierge in large contact centers, not only in routing contacts between departments but in gauging intent and collecting relevant information before a contact. As a result, the employee can move the contact forward without having to search for relevant knowledge; the ZVA has collated it for them.

Yet, while few can offer such an AI concierge that breaks the boundaries of the contact center, Zoom’s fellow CCaaS-UCaaS provider, RingCentral, released a similar solution in February 2025.

Within three months, 1,000+ businesses deployed the RingCentral AI Receptionist (AIR), highlighting the market’s desire for such solutions.

Tim Banting, Head of Research & Business Intelligence at Techtelligence, picked up on this and told CX Today:

Both Zoom and RingCentral are directing their AI efforts toward practical business solutions rather than the more mundane, table-stakes AI features like meeting summaries, rewriting messages, and transcripts. This demonstrates both companies’ commitment to meaningful R&D.

However, where Zoom may differentiate from RingCentral is in the broader capabilities of ZVA, a comprehensive conversational AI solution that many contact centers have already deployed. These businesses may leverage the new integration to extend their implementation and bolster their swarming strategies.

Additionally, Zoom promises a deployment “within minutes”, with a no-code configuration. Meanwhile, the ZVA currently supports conversations in English, French, German, Portuguese, Japanese, and Spanish, although Zoom pledges that support for more languages is “on the way”.

More Additions to the Zoom Enterprise Communications Platform

Across its enterprise communications platform, Zoom has made several other announcements.

Firstly, it has become “among the first” tech providers to integrate OpenAI’s GPT-5 into its AI stack. Yet, most other news flashes concern new platform features. Here are the three most notable.

1. AI Companion Auto-Scheduling

AI Companion is the virtual assistant that assists users across Zoom’s platform. It’s currently available at no extra charge.

Zoom has bolstered the solution with a meeting scheduling skill, so it considers everyone on a meeting invite list – including internal employees and external partners – and spotlights the best-placed time.

That “best-placed time” isn’t only based on calendar availability. Indeed, the AI Companion also tracks time zones and out-of-office notices.

From there, it sends the invites and keeps tabs on responses. When someone declines, it suggests an alternative time to the organizer, who can book the meeting as quickly as possible.

That’s the aim of this solution: to remove the tedious back-and-forth of arranging meetings.

2. The All-New Zoom Hub

Within Zoom Workspace is a new asset Hub, where users can store meeting summaries, documents, whiteboards, clips, and more.

Employees can navigate these files via the AI Companion, which spotlights insights from assets based on natural language commands. That means employees don’t need to jump between tools to find what they need.

Moreover, Zoom hopes its new Hub will help teams stay organized, quickly surface assets during conversations, and quickly save collaborative content drafts created during meetings.

3. A Refurbished Zoom Team Chat Experience

Finally, Zoom has embedded AI Companion into the Zoom Workplace mobile app’s Team Chat compose bar.

As a result, it hopes users can prompt the AI Companion to surface draft messages and help them catch up on what they missed.

Moreover, when using Team Chat on a desktop, users may summarize files by clicking on a new “summarize icon” when hovering over a file stored within Zoom.

Last month, Zoom made many more platform enhancements geared toward CX personnel. Here’s the rundown: Zoom Drops an Auto Dialer, Expands Its Portfolio for Sales and Revenue Teams

Users tasked LucyPhone to take their place in a phone queue while they waited for a human representative. The app relied on customer service agents to prompt the bot to alert the caller that they’d reached the front of the line. Many agents, upon hearing a robotic voice, simply hung up. The Inland Revenue Service went further, instructing all its agents to terminate any calls from LucyPhone bots.

The app was the latest iteration of vendor relationship management (VRM), a term first coined in 2000 and popularized by blogger and journalist Doc Searls.

“Conceptually, we’ve been here for decades, this notion that consumers need a way to have a force multiplier on their side in the same way that brands use technology as a force multiplier,” Ian Jacobs, VP and Lead Analyst at Opus Research, tells CX Today.

However, that concept was never followed by a concerted technological movement, according to Jacobs, until the recent introduction of generative and agentic AI brought the idea closer to reality.

The Quickening Pace of Machine Customer Development

This year, several major companies have launched significant forays into machine customer technology. In January, Google unveiled an experimental new feature called “Ask for Me,” which enables users to task an AI agent to call businesses and make enquiries on their behalf. And in July, Walmart announced plans to introduce AI-powered “super agents,” intended to improve customer experience.

That trend is expected to continue. Gartner predicts that by 2030, 15-20% of revenue will come from machine customers.

“I expect that these capabilities will continue to advance quite rapidly over the next two to three years,” Daniel O’Sullivan, Senior Director Analyst at the Gartner Customer Service Practice, predicts. “Younger generations, millennials, and Gen Z, have told us that when it comes to, for example, trying to resolve a customer service issue, their preferred starting point is to use a generative AI channel of some kind.”

As more people delegate tasks to agentic AI, customer service providers will face the same choices agents encountered when LucyPhone appeared on the other end of their calls in 2010. Organizations may follow the IRS’s example and refuse to interact with non-human customers.

Given the compliance, privacy, and legal issues that may arise, that would be the simplest solution, but O’Sullivan says they run the risk of falling behind competitors. “I think you’re battling against the tide if you dig your heels in and say that’s what you’re going to do, because customers will do whatever they want,” he says, adding that customers will see this as a way to make everything “easier and more convenient.”

How Will Machine Customers Impact CX?

The rise of machine customers could significantly shift how organizations provide customer experiences. Call centers can expect an increase in the volume of incoming calls, as consumers use tools like Google’s Ask for Me to make enquiries they don’t have time to pursue. But more worryingly, the value of their calls may decrease sharply.

Human customers offer some very tangible advantages that have, until now, been taken for granted. In a conversation with a human, agents can reinforce relationships, upsell products and services, and receive valuable feedback.

“[Organizations] might wake up to a moment where they no longer really have a connection with their customers at all, and they don’t necessarily even know what their customers want, and so then they’re kind of flying blind, and their opportunities to upsell and drive revenue, retention and growth, become much more challenging,” O’Sullivan says.

An influx of machine customers may also necessitate a redesign of infrastructure across organizations. For example, websites are currently built to appeal to the human eye, drawing them in through thought-out design and a carefully constructed customer journey. AI agents simply want data. The same applies to call centers.

“Companies will need to rearchitect their customer experience, which was going to be personalized, ensuring that it’s designed not just for emotion or empathy because that’s what the humans were taking care of,” Rishi Rana, CEO of Cyara, tells CX Today.

“This marks a fundamental shift from a human-centric customer experience CX model to one that also supports machines as decision makers,” he adds.

Many Hurdles Remain for Machine Customers

Although their increased use appears inevitable, the introduction of machine customers faces significant challenges.

The first is interoperability. Today, an AI agent can recommend restaurants based on a user’s dietary preferences and other factors. However, it can’t purchase ingredients for a homemade meal using the same personal data. “The first steps are there: the intelligence to understand you, your preferences, your needs, and take instructions with the right kind of guardrails are there. But the commerce part isn’t,” Jacobs says.

That issue will most likely be ironed out in the future as interoperability is usually achieved over time. SMS messages initially faltered between network carriers and operating systems, but now work flawlessly.

Privacy, legal, and compliance issues cause more concern. Jacobs asks:

How do they trust that the bot placing the order on Instacart is actually me?

He continued: “If it’s only buying $45 worth of stuff. Is that a big deal? Maybe we’ll let that go through. If all of a sudden it was $800 and it’s still a commerce purchase with something that needs a physical product that needs to be shipped, maybe you’re less apt to ship it until you get some human confirmation, which kind of ruins the point of the agentic nature of it.”

Should machine customers overcome these issues, there will be fierce competition in the space. Companies like Google, Microsoft, OpenAI, and others will fight it out for market dominance, while many organizations may take the same approach as Walmart and offer their own agents rather than deal with a host of external bots. “I personally think Google may be in the best place to win here, because they’ve already got their ecosystem, which contains a lot of your data already,” says O’Sullivan.

Whoever comes out on top, the CX industry must be prepared for a new era of machine-to-machine interaction, where holding a place in line is the very least of a bot’s capabilities.

The CEO made the comments last week during the Fed’s Integrated Review of the Capital Framework for Large Banks Conference in Washington.

Speaking to Michelle Bowman, Vice Chair of the Federal Reserves, Altman first stated:

There are cases where entire classes of jobs will go away, [and] there are entirely new classes of jobs that will come.

When pressed on what some of those lost jobs might be, he used customer support staff as an example of a role that will be “totally, totally gone.”

Already, various tech companies building AI agents for service have had significant success in automating customer contacts.

For instance, Salesforce and ServiceNow claim to have mechanized 85 and 80 percent of their internal customer queries, respectively.

Altman underscored this rapid progress in customer-facing AI and, like Oracle, envisaged a future where service is entirely automated.

The CEO stated: “A couple of years ago, you’d call customer support, you’d go through a phone tree, you’d talk to four different people, they’d do the thing wrong, you’d call back again, you’d wait through it… It’s like hours of pain, a ton of time on hold, and the thing you want doesn’t happen. [It was a] very frustrating experience.

Now, you call one of these things, and AI answers. It’s like a super smart, capable person. There’s no phone tree, there’s no transfers. It can do everything that any customer support agent at that company could do. It does not make mistakes. It’s very quick. You call once, and the thing just happens. It’s done. Answers right away. Great.

“So, that’s a category where I would just say, you know what, when you call customer support, you’re going to be talking to an AI, and that’s fine.”

While Altman may have a point in the longer run, his assessment of today’s chatbots doesn’t align with most consumers and industry practitioners…

The End of Human Service? Studies Say That’s a Distant Prospect

Despite Altman’s prediction, research firm Cavell recently found that demand for human contact center agents will grow from 15.3 million in 2025 to 16.8 million by 2029.

While AI may have tempered that increase, its short-term threat to rep jobs appears minimal.

Gartner’s research backs this up. Last year, the analyst found that most service leaders only expect headcount reductions of five percent or less due to advances in generative AI.

Alternatively, a Microsoft report found that “customer service reps” is the sixth most at-risk job from the rise of AI. It followed interpreters/translators, historians, passenger attendants, sales reps of services, and writers/authors.

However, this threat may be longer-term than Altman’s statements suggest.

Also, studies emphasize an overwhelming preference for human customer service. For instance, one report published in early 2025 found that 81 percent of customers would rather wait a minute or more for support from a live person than interact immediately with an AI assistant.

Today’s customer service teams share this negative sentiment towards customer-facing AI. Indeed, Gartner found that three in five human agents don’t recommend self-service, with the research firm hinting that this negativity is driven by customer feedback, more so than any threat bots pose to their job security.

After all, many reps often interact with customers who feel like they had to break out of AI jail to get through to them, pounding “zero” on their keypad and yelling “agent” into the phone.

As these experiences persist, a fully automated customer service function is almost impossible for many to envision. However, with the pace of AI innovation, predicting the future is trickier than ever before.

The agent is capable of doing real, complex work, using a computer. To do so, it switches between thinking and acting while using tools like the web, spreadsheets, slides, and more.

Thanks to this capability, ChatGPT agent may perform many office-based tasks, such as building spreadsheets, creating slideshows, and developing meeting agendas.

However, it can also execute tasks on behalf of consumers.

OpenAI shared an example of a person preparing for a friend’s wedding. They gave ChatGPT agent the following prompt:

Find outfits that match the dress code, consider the venue and weather, propose a few options in a mid-luxury range, suggest hotels, and find a thoughtful gift.

The ChatGPT agent first clarified the wedding date and location. It then performed those tasks on a virtual computer. As it did so, the user watched from their device, with a view of the agent’s chain of thought, i.e., what it’s thinking as it works. Importantly, the user could intervene whenever they wanted.

From the demo, OpenAI showcased how consumer-facing agents – like ChatGPT Agent – could redefine how people find products and services. Yet, the AI juggernaut also showcased how these agents could transform how customers communicate with and buy from organizations.

How ChatGPT agent Communicates with Businesses on Behalf of Customers

First, consider how ChatGPT agent works. To browse the web, the agent builds on two previous OpenAI innovations: Deep Research and Operator.

Like Deep Research, it can quickly read and search web pages. Meanwhile, it can interact with UI elements – i.e., clicking, dragging, and filling out forms, etc. – like Operator.

By interacting with UI elements, ChatGPT agent can hop on a live chat widget and interact with a business on a customer’s behalf. It may also fire off emails.

As a result, contact center reps may soon find themselves interacting with AI much more frequently, which should provoke some tricky internal conversations around security and compliance.

Moreover, as many businesses have deployed their own AI agents across live chat and email, ChatGPT agent beckons a future of “machine-to-machine” customer service (more on this below!).

While OpenAI did not single out this use case, it stressed that ChatGPT agent will ask for confirmation before taking important steps, like sending a message or email to a business.

How ChatGPT agent Buys from Businesses on Behalf of Customers

When launching ChatGPT agent, Sam Altman, CEO of OpenAI, underscored the possibility of a consumer prompting the agent to buy an item. The user can even give the agent their credit card information, so it completes the purchase autonomously.

As a result, ChatGPT agent can effectively manage end-to-end customer journeys, finding products, communicating with businesses, and buying from them.

While that’s an exciting possibility, many will be cautious about the agent falling for scams and Altman admitted that’s a real risk.

OpenAI has taken steps to mitigate such risks. For instance, it allows users to intervene at key moments, such as when typing in credit card details.

However, as Altman stressed: “It’s a new way to interact with AI, [and] with that comes a new set of potential attacks.

“Society and technology will have to evolve together to mitigate risks we can’t even fully anticipate yet, especially as people begin to do more and more work through AI agents.

We encourage users to be proactive in how they share their information. For example, if something is highly sensitive, it’s best not to share it. Instead, use features like “Takeover Mode” to input sensitive details, like credit card information, directly into the browser, rather than giving that information to the agent.

Nevertheless, OpenAI encouraged risk-aware consumers to try out the ChatGPT agent, which they can do via the app by clicking the “Tools” menu and selecting “agent”. Alternatively, users can just type “agent” into the composer bar.

Check out the video below for more from Altman and his team on the launch.

Concerns Over OpenAI’s Bid to Reimagine Online Customer Experiences…

As consumers use ChatGPT agents to search for and buy products, businesses will likely share the same concern: how do we know it’ll be fair?

Given how Altman recently mulled over the possibility of adding adverts to ChatGPT, such concerns have their merits.

However, soon after making its agent announcement, OpenAI confirmed that it will look to take a cut of product sales made inside ChatGPT.

In doing so, the AI giant allayed fears that “search-to-product matching” will be based on who pays the most. Instead, relevance seems to be what will drive clicks.

While that may challenge Google’s $200BN advertising model, it also presents an opportunity for brands focused on building content relevant to what people are actually searching for.

Interestingly, as consumers interact more with ChatGPT and it gets a better understanding of their preferences, it could – one day – offer the most relevant searches to them as an individual.

Nevertheless, for now, marketing teams may wish to lower their reliance on third-party ad clicks and instead rethink the first-party content and product data they make available to ChatGPT.

Meanwhile, customer service teams will also have lots to think through…

Preparing for a Future of Machine-to-Machine Customer Service

In contacting businesses on behalf of consumers, ChatGPT agent is another step towards machine-to-machine customer service.

While that may be an exciting prospect for customers sick of waiting on hold, so far, only 50 percent of CEOs have begun to develop a strategy for machine customers, per Gartner. That’s a problem.

For instance, how can they authenticate that the AI agent is acting on behalf of the customer? What tasks should an AI agent be allowed to accomplish? Should the machine customer have a spending limit?

Most businesses haven’t yet addressed such process and policy challenges, but they’ll soon need to.

During the conversation, host Andrew Mayne quizzed Altman over the potential for OpenAI to insert advertising into the much-loved AI model.

Many have touted the move, with the company projected to burn through $26BN and accumulate $14.4BN in losses this year, per the New York Times.

Addressing the speculation, Altman claimed that he’s “not totally against” the idea. Yet, they aren’t sure what an advertising product would look like.

“I can point to areas where I like ads,” said the CEO. “I think ads on Instagram are kind of cool [and] I’ve bought a bunch of stuff from them. But I think it would be very hard to get it right; it would take a lot of care.”

Altman then underscored the high degree of trust in the independence of ChatGPT’s outputs, and appeared unwilling to break that.

Indeed, the OpenAI head honcho believes faith in web search has fallen, as with social media, because “you can tell you’re being monetized.”

He continued: “How much do you believe you’re getting what the company truly thinks is the best content for you, versus something designed to interact with ads? There’s a psychological effect there.

For example, I think if we started modifying the output stream from the LLM (large language model) in exchange for who paid us more, that would feel really bad, and I would hate that as a user. That would be a trust-destroying moment.

Of course, there are alternative methods, such as inserting adverts outside the ChatGPT stream. Yet, Altman stressed: “It would have to feel really useful to users and really clear that it was not messing with the LLM’s output.”

The idea of adverts becomes even more complex, given OpenAI’s recent move to release a new shopping experience, where users can find products/services, compare them, and follow a link to make the purchase.

For those unfamiliar with the experience, check out the video below.

Reports of OpenAI teaming up with Shopify to deliver an end-to-end commerce experience within ChatGPT underscore its intention to build upon this.

In doing so, ChatGPT may soon become the go-to place for many shoppers, with it already getting 5.24BN hits each month, per SEMrush.

That prospect is exciting, but could cause concerns if OpenAI introduces an advertising product. After all, with ads, consumers may question whether their search results and comparisons are independent.

Thankfully, OpenAI appears to be against such actions, for now.

More Moves By Open AI to Transform Customer Experiences

OpenAI’s innovation team hasn’t taken the summer off, releasing a series of data connectors last month that link ChatGPT with popular business applications.

Amongst those apps is HubSpot, the widely utilized CRM offering.

With its connector, brands can pull customer data into ChatGPT, run deep research queries against it, generate new data, and pull that back into the CRM.

In doing so, CX leaders using HubSpot may run sophisticated analytics projects via the familiar ChatGPT interface to refine customer targeting strategies, spot new sales opportunities, forecast staffing needs, and more.

On the launch, HubSpot’s CTO declared it a “big day in HubSpot history.”

However, the move asked some uncomfortable questions for conversational intelligence providers, with some even suggesting it signaled “the death of Gong.”

That’s a question up for debate. Yet, it underscores how ChatGPT is changing the landscape, not just in terms of how customers interact with brands but in how brands evolve their tech stacks.

Enterprises need platforms that align employee and customer experience, enable omnichannel interactions, and offer access to the latest AI tools – all while still delivering enterprise-grade compliance and global scalability.

This year, the vendors plucked from the CX Today contact center marketplace may be familiar in name, but their roadmaps are evolving, with agentic AI, live analytics, seamless UC integration, and so much more. No more clunky legacy systems, now it’s the age unified contact center platforms powered by dynamic agents and data-driven decisions.

This guide dives into the best contact center vendors in 2025, assessing how each stacks up on innovation, enterprise utility, and real-world CX impact.

The Top Contact Center Vendors in 2025

• • 8×8
  • AWS
  • Avaya
  • Cisco
  • Content Guru
  • Enghouse Interactive
  • Evolve IP
  • Five9
  • Genesys
  • Google
  • Microsoft
  • NICE
  • Odigo
  • Puzzel
  • RingCentral
  • Salesforce
  • Sprinklr
  • Talkdesk
  • Twilio
  • UJET
  • Vonage
  • Zoom

The Top Contact Center Vendors for CX Leaders

Contact center vendors come in a lot of shapes and sizes right now, from cloud-focused leaders, to flexible innovators that build systems designed for specific use cases. These are just some of the companies making waves right now.

8×8

8×8 continues to stand out as a top contact center vendor with a focus on flexibility. It was one of the first companies to integrate UCaaS and CCaaS, and one of the earliest cloud (CCaaS) pioneers. 8×8’s contact center combines omnichannel communication with AI-powered features, like background noise suppression, real-time language interpretation, and even accent localization.

ML-powered global reach ensures 8×8’s tech delivers seamless experiences around the globe. Flexible API and integration options let businesses expand without compromise. Realizing visions can be extremely complex, and 8×8 has endured turnover in its C-suite. Yet, current CEO Sam Wilson has heightened the company’s focus on execution.

In doing so, 8×8 has aligned itself closely with the Microsoft Teams ecosystem. That has helped further its market positioning in recent years. Don’t expect this to change in 2025, as 8×8 continues to double down on its core competencies, bring its CPaaS capabilities further into the fold, and engage deeply with the midmarket.

AWS

Amazon Connect started as a journey to build a dedicated AWS CX solution. Now, it’s one of the most flexible and scalable contact center systems in the market. For companies in search of the top contact center vendors, AWS delivers an excellent choice between out-of-the-box simplicity, and high levels of customization.

Generative AI is woven into the platform via Amazon Q and advanced Contact Lens features. This helps agents with real-time responses and post-call categorization, streamlining supervision and training. The platform also embraced omnichannel depth: new support for voice, chat, SMS, video, and even WhatsApp ensures enterprise flexibility.

In addition, the fact that Amazon uses this solution across its 70,000-agent contact center allows for a strong testbed for any innovation to come from AWS. The refinement of capabilities before release builds trust in the vendor, an excellent trait in a competitive environment.

Avaya

Avaya is in rebuild mode. The company’s focus for 2025 is clear: support its existing enterprise customers and make the transition to modern contact center infrastructure as smooth as possible. That means less hype, more practicality.

At the centre of it all is the new Infinity platform. It pulls voice, chat, email, and messaging into one environment, built to run wherever it’s needed. That includes on-prem, in the cloud, or somewhere in between. For long-time Avaya customers, that kind of flexibility is valuable. Many aren’t ready to move everything to the cloud, and with Infinity, they don’t have to.

One standout feature is its no-code workflow builder. It’s a visual tool that lets business teams adjust customer journeys without pulling in developers. Routing, sentiment analysis, and post-call actions can all be handled in the same space. For organizations with deep investments in legacy systems, Infinity offers a way forward. It’s not a rip-and-replace story. It’s a steady evolution, aimed at helping large enterprises modernize at their own pace.

Cisco

Cisco remains a heavyweight in the top contact center vendors arena. Today, it’s combining enterprise-grade scale with aggressive AI innovation. Its Webex Contact Center now includes AI Agent Studio and Webex AI Agent, capable of handling 24/7 self-service via conversational intelligence, summarizing past conversations, and suggesting agent responses in real time.

The integration of Cisco’s CCaaS and CPaaS solutions will help the vendor in moving many of its large legacy base to the cloud. After all, it allows many of these larger customers to replicate custom integrations in the cloud, minimizing some of that migratory strife.

Cisco can link more seamlessly to point-of-sale, ERP, and in-house solutions, going beyond the typical CRM integrations. In addition to this, Cisco also aims to differentiate itself with its deep, adjacent security and networking portfolio, alongside its employee-serving technologies.

Content Guru

Among the top contact center vendors, Content Guru has developed a reputation for moving high-complexity, on-premise contact centers to the cloud, a testament to the robustness and resilience of its offering. It was recently Europe’s solo representative in Gartner’s CCaaS Magic Quadrant.

Content Guru’s storm platform stakes a strong claim among the best CCaaS systems for enterprise and public-sector users. With unmatched availability and scalability, storm handles up to 75,000 digital agents and 20,000 voice agents in major use cases.

The vendor is also one of a minority that has obtained a FedRAMP designation from the US Government and – at the time of writing – is the sole vendor to achieve its high impact “In Process” designation. Achieving the highest impact level certifies Content Guru’s ability to protect the most highly sensitive data within government cloud environments.

Enghouse Interactive

Taking a different approach to the likes of AWS, Enghouse has predominantly focused on growing its portfolio by acquiring other companies. Consequently, it has the advantage of offering a broad suite of contact center solutions.

Such an approach is appealing to enterprise customers who appreciate the safety of a large portfolio of new solutions to draw from, including everything from workforce engagement management (WEM) to unified communications (UC). Enghouse also stands out as one of the top contact center vendors for Conversational Intelligence and automated QA tools.

Its Contact Center for Enterprise solution supports seamless multichannel blending: voice, chat, digital, designed to route customers correctly the first time.  Early 2025 enhancements include native integration with Microsoft Teams Phone via Azure Communication Services, available for TAP customers. This tight coupling enables agents to use Teams for queuing and call handling directly within Enghouse’s platform, offering a unified experience built for hybrid teams.

Evolve IP

Evolve IP embeds itself into the broader customer experience environment thanks to its broad integration strategy. Its adaptability to other solutions – across the UC and CRM space especially – will benefit enterprises already set up on other cloud-based systems.

Flexibility is a standout point.  Evolve IP’s XTIUM Contact Suite enters 2025 with a renewed partner ecosystem focus, delivering cloud-native features like omnichannel routing, rapid deployment, and hybrid cloud flexibility. Their platform enables resellers to label and price solutions, with Evolve IP handling infrastructure and backend services.

As a full-service cloud partner, Evolve IP helps enterprises offload complexity while gaining a compliant, scalable foundation. The reseller-driven model offers flexible commercial paths, while feature updates in early 2025 enhanced agent tools and backend reliability.

Five9

As an early advocate for CCaaS, Five9 has developed a significant market presence and trust in its brand. Five9 stands out as a champion of “agentic CX,” introducing AI Agents that can reason, decide, and act autonomously. These agents are backed by “AI Trust & Governance” to ensure transparency, compliance, and auditability, crucial for enterprises in regulated sectors.

AI-powered routing, real-time analytics with Spotlight for AI Insights, and expanded global availability via Google Cloud Marketplace position Five9 among the top contact center vendors this year. A deep partnership with Microsoft Teams brings bi-directional presence integration to agents and UC users alike, while tight ServiceNow integration enables end-to-end AI-driven workflows.

Five9’s commitment to human-centered design, balancing autonomy with agent support, makes it a strong pick for enterprises aiming to elevate CX while maintaining control and clarity.

Genesys

Genesys has done a sterling job of migrating existing enterprises onto the cloud through playbooks and sharing best processes as a support service. The top line for this vendor in 2025 is: don’t expect anything radical unless it spins off and becomes an IPO.

That said, it’s still gaining steam as one of the top contact center vendors, thanks to a close working relationship with Salesforce and ServiceNow. These collaborations have allowed the vendor to position itself ahead of the curve in terms of CRM-CCaaS integrations. Genesys is also evolving its AI-driven orchestration and personalized engagement capabilities.

In early 2025, Genesys expanded its AI for Supervisors suite, enabling managers to cut quality evaluation time by up to 40%, multilingual review time by 25%, and administrative overhead by nearly 40%. Organizations are also adopting Genesys for its agentic AI – a move to autonomous digital workers that handle workflows end-to-end, not just script-following bots.

Google

Google is quietly stepping up its game in the top contact center vendors space. At Cloud Next 2025, it unveiled tools like Agent Space and Agent2Agent frameworks, making multi-agent, multi-model AI orchestration a reality. The updated Contact Center AI platform now includes enhanced Salesforce ICU support, improving locale and date/time formatting across global deployments too.

Google also continues to refine its Customer Engagement Suite. It’s adding human-like voices, CRM connectors, and emotion-sensing capabilities, showing a growing maturity in enterprise-grade CCaaS. Verizon recently integrated Gemini-powered chat into its support flows, demonstrating real-world demand.

Although it hasn’t yet dominated the Gartner leaderboards, recent moves signal Google’s push to be a strong player. For global businesses seeking flexible, developer-friendly, AI-driven contact center capabilities, Google’s CCAI platform is worth watching.

Microsoft

Microsoft finally made its big CCaaS move last year with the launch of the Dynamics 365 Contact Center, its “Copilot-first” platform. The offering is attractive to current users of Microsoft’s CRM solution: Dynamics 365 Customer Service, with Copilot helping to pull the platforms together and unify the service environment.

Companies already get AI-driven routing, unified case management, real-time transcription, live translation, and embedded Teams collaboration for seamless agent and knowledge workflows. Yet, Microsoft undoubtedly wishes to reach a bigger audience in 2025, and bringing agentic AI into the space is its most compelling tactic.

It’s already begun adding native AI agents to the platform, and giving companies opportunities to embed and build their own AI solutions. Plus with new connection options for third-party vendors looking to leverage Microsoft Teams Phone, Microsoft is continuing to bet on versatility.

NICE

NICE is pushing hard to maintain its reputation among the top contact center vendors with its reimagined CXone Mpower platform. Neck-and-neck with Genesys, NICE leads the CCaaS market in terms of revenues. Key to this is the vendor’s early move to embrace CCaaS, its aggressive use of AI, and numerous success stories that help prove its ROI.

Couple this with its gold-standard WEM, and it’s no surprise NICE is at the forefront of various industry research reports, including the Gartner Magic Quadrant and Forrester Wave. Additionally, NICE has lots of different adjacent solutions, such as robotic process automation (RPA), compliance, and UCaaS tools, which are adjacent to the contact center market.

This means that they can replace a lot of different solutions when they enter a contact center and converge the customer service environment. Plus at Interactions 2025, NICE showcased how “agentic AI” runs the full spectrum, from intent to resolution, automating entire workflows through integrated audio, digital, and knowledge layers, earning new attention from enterprises.

Odigo

Odigo may fly under the radar compared to hyperscalers, but it’s firmly in the mix as one of the top contact center vendors for European enterprises and public sector clients. The company popped onto the CCaaS scene by spinning out of Capgemini.

Having kept close ties, Odigo can leverage Capgemini’s various subsets of CX expertise to offer enterprises deep consulting services that may aid their transformations. Its Extended Contact Center model allows flexible licensing for occasional users, back‑office, branch staff, or advisors, supporting seasonal use at lower rates.

Meanwhile, its AI Orchestrator engine, voice+digital channel support, open APIs, and SightCall integration provide rich, scalable capabilities, designed for compliance-heavy industries.

Puzzel

Like Odigo, Puzzel is an established Europe-first contact center vendor that strives to differentiate by being a close transformation partner. Its optimization program ensures that it’s not one of those providers that implement a solution and then walk away. That continuous support is massive.

Additionally, Puzzel is expanding beyond the core facets of CCaaS with various other solutions like sales intelligence systems for insights into revenue opportunities and digital engagement. It also introduced a callback display feature in June 2025, which sends customers an SMS link allowing them to view their queue status live, and cancel if needed, reducing abandonment.

Puzzel’s focus on AI-powered agent assist, intelligent routing, and comprehensive performance metrics also means agents spend less time toggling systems and more on valuable customer engagement

RingCentral

Since the release of the Ring CX contact center solution, RingCentral has leaned further into its vision of becoming the communication layer across an enterprise, including contact centers. By combining the CCaaS solution on one platform with its UCaaS and conversational intelligence offerings, it bridges the contact center and the broader business.

As one of the top contact center vendors this year, RingCentral also invests heavily in AI. Their AI‑led RingCentral AI Receptionist has shown strong ROI, cutting inbound call handling time by half and helping agents focus more on revenue-generating interactions.

The broader RingCX AI enhancements offer deeper analytics, AHT reduction, and better onboarding for new agents, all promoting efficiency and satisfaction. RingCentral Rooms also now features high-fidelity multi-stream audio and advanced camera presets, great for video CX.

Salesforce

The Salesforce Contact Center is little more than a routing engine layered over its Service Cloud CRM application. So, why does it feature on this top contact center vendors list? Because Service Cloud is an incredibly powerful solution, especially when placed within the broader Salesforce ecosystem.

The Spring ’25 update pushed Agentforce Service into GA, bringing AI-supported real-time supervision, case routing, and field-service automation. The Summer ’25 release enhanced that suite further, enabling AI agents to surface visuals, media, and rich context during interactions across Lightning, mobile, and Slack apps

Companion updates to Service Cloud Voice ensure fully featured call center UIs can be updated directly via Salesforce’s deployment tools.  Most notably, the Salesforce-Amazon Connect combined offering hit general availability in March 2025, merging Amazon’s voice and digital interactions directly within Service Cloud.

Sprinklr

With its legacy of being the social media provider for many enterprises, Sprinklr’s aggressive move into the contact center and conversational AI space has garnered significant attention. From digital twin agents that replicate human agents to advanced VoC features, it’s not a vendor that avoids nudging the innovation needle, either.

Looking to build on the momentum created from securing deals with companies like BT and Deutsche Telecom, this vendor will likely see further developments in 2025. As it does so, expect Sprinklr to bolster its focus on execution, especially after naming Rory Read as its new CEO, someone with a deep understanding of the contact center space.

Already, Sprinklr is making progress as one of the top contact center vendors, with more generative AI capabilities, and flexible automation. It was even named a top performer by Gartner in the last Magic Quadrant.

Talkdesk

Talkdesk is very big on sector-specific solutions, packaging individual clouds with oven-ready workflows and AI tuned specifically for that industry. The vendor is also focused on supporting highly customized CX environments, with a Talkdesk Embed module allowing businesses to place their core functionalities within a tailored CX environment.

In 2025, new capabilities like AI Launchpad’s redaction controls and generative AI guardrails add privacy safeguards, crucial for regulated industries  Talkdesk also garnered industry acclaim: receiving the 2025 AI Agent Product of the Year award and earning recognition for its CX performance.

With strong enterprise integrations (CRM, analytics, workforce management), high availability, and AI-powered agent workflows, Talkdesk delivers a turnkey, intelligent top contact center platform for enterprises that need robust tools and fast outcomes.

Twilio

Similar to AWS, Twilio first released its CCaaS platform – Flex – as a set of building blocks. It allows contact centers to develop unique operations for companies’ specific needs. However, with the company somewhat sidetracked by its massive Segment acquisition, Flex hasn’t enjoyed the same growth as Amazon Connect.

Thankfully, the company has pivoted recently and now again appears more intent on making its mark across the contact center space. Positioned firmly as one of the best contact center platforms, Flex offers a low-code toolkit for embedding omnichannel journeys: voice, chat, SMS, email, and messaging apps, into custom workflows.

2025 updates add real-time queue metrics and alerts in supervisors’ dashboards, enabling immediate intervention when service levels waver Closer integration with Segment CDP and generative AI previews signal Twilio’s trajectory toward data-rich, intelligent engagements.

UJET

UJET has taken a unique approach to contact centers. Its CCaaS solution is smartphone-oriented, as it believes contacting customer service should feel no different from messaging a friend or family member on WhatsApp or calling them.

Despite having developed this architecture years ago, the approach remains unique within the contact center space. UJET also allows users to orchestrate the ideal experience for each significant reason customers reach out to the business, blending various types of AI.

Teams can experiment with real-time agent assistance, forecasting, sentiment analysis, and virtual agents for frictionless in-app support. Plus, the has a close relationship with Google, and Microsoft, equipping it with early access to the latest AI models and accelerating its innovation curve.

Vonage

Vonage is another vendor merging CPaaS and CCaaS. In its case, the vendor can leverage the vast networks and 5G capability of Ericsson, its parent company. As such, Vonage differentiates in its mobility. Like many of the top contact center vendors, Vonage has a strong partnership ecosystem.

Its close ties to Salesforce are notable, yet – more differentiative – is its co-innovation relationship with SAP, another large enterprise CRM provider. In 2025, the contact center offering introduced various AI capabilities, virtual assistants for self-service, dynamic IVR routing, real-time speech analytics, and knowledge-base recommendations.

Other updates introduced granular control over email journey types and agent interaction with enriched customer context, streamlining workflows and broadening channel coverage. Vonage’s microservices-backed architecture and compliance support (PCI, GDPR, etc.) suit modern CX requirements too.

Zoom

Zoom is a relative newcomer to the contact center sphere, yet has fast established a deep install base of 1,250+ customers. Much of that business stems from customers within its broader base and reputation for delivering easy-to-use software. However, it also comes as Zoom has developed a rapid innovation cycle.

Its Contact Center offering leverages native integration with Zoom Meetings, Phone, and Team Chat to deliver unified agent experiences. Recent upgrades include real-time sentiment dashboards, AI-powered wrap-up suggestions, and enhanced video-first routing.

Zoom is also doubling down on top contact center vendor workflows for frontline-heavy industries. Advanced callback features and mobile engagement tools support agents on the go. Integrated knowledge bases and searchable transcripts improve first-contact resolution.

Choosing the Top Contact Center Vendors in 2025

Comparing contact center platforms used to mean looking at channels. Voice, chat, email. That’s changed. Now it’s about orchestration. Can the platform move between those channels without losing context? Can it automate handoffs, assist agents, and deliver something useful to supervisors at the same time?

In 2025, most platforms offer some version of AI, automation, and omnichannel support. But how they use these features, and how well the platform fits with business goals is what matters. The same goes for integrations. Everyone says they have them. Not all of them work the way you need.

For companies still struggling, CX Today offers resources designed for clarity:

• Dive deeper into the data: Download our latest CCaaS research reports to uncover market trends, vendor comparisons, and real-world adoption stats.
• Join our CX Community: Connect with CX leaders, decision-makers, and collaboration experts to share strategies and success stories.
• Discover live demos & events: Engage with vendors face-to-face at upcoming events, experience live demos, and network with peers who’ve walked the path.
• Master the procurement process: Use our Ultimate CX Buyer’s Guide to navigate every stage, from requirements gathering to implementation planning.

The future of customer engagement demands platforms that are intelligent, integrated, and outcomes-driven. With CX Today, enterprises can make sure their CX strategy is ready for what’s next.