What 2025 Data Tells Us About the Future of Chatbots in CX

The Gist

• Speed over savings. Faster response times — not cost cutting — are now the top reason CX leaders invest in chatbots.
• Product guidance wins. Nearly 90% of CX leaders say chatbots offer the most value when guiding customers to products and services.
• Trust, not tech, is the blocker. Privacy concerns and limited expertise top the list of chatbot adoption barriers — not customer resistance.

As AI adoption accelerates across industries, US customer experience (CX) leaders are increasingly focusing on chatbot technology — and exploring how chatbots improve customer experience in measurable ways.

To find out what 396,226 CX leaders' opinions in the US thought about the impact chatbots have on customer experience, AI-driven audience profiling was used to synthesize insights from online discussions over a year ending July 7, 2025, to a high statistical confidence level. The findings reflect a sector in transition that’s actively reshaping the human-AI dynamic at the frontlines of customer engagement.

We're also seeing growth in the use of chatbots for customer experience, particularly in service and support channels. According to the CMSWire 2025 Digital Customer Experience (DCX) Report, we do see a noticeable rise in the numbers using generative AI in direct “Customer service/Chatbots” (up from 30% to 40%), perhaps reflecting generative AI starting to be implemented in different platforms and products.

Chatbot Adoption Surges Alongside Generative AI

As far as technologies that have grown in adoption this year, chatbots (51%) checked in for 2024 at the 17th most common answer, but now in 2025 is the 12th and used by a majority of respondents for the first time, again reflecting AI's unstoppable march across the digital customer experience tech landscape.

However, we were surprised to see “customer-facing chatbots/conversational experiences” so low in the list of investment priorities (19%) — ranked the second lowest choice — given that the leap in AI capabilities is likely to make chatbots significantly more sophisticated.

Key Chatbots for CX Data Takeaways

Expand the section below for a concise summary of research findings.

Related Article: The Contact Center’s New MVP: AI Chatbots That Know When to Escalate

What Primary Goal Drives CX Leaders' Interest in Chatbots?

23% of US CX leaders are interested in chatbots because they offer faster customer responses 

CX leaders’ interest in chatbots depends on the outcome that matters most:

Speed of Service Outpaces All Other Motivators

In 2024, 82% of consumers stated they would rather use a chatbot than wait for a customer representative to take their call. This reflects the primary goal behind the use of this technology for US CX leaders. Twenty-three percent of those whose opinions were analyzed said that faster customer support was an important factor in their interest in chatbots and 8% said it was definitely a factor. However, 11% also said that it might not affect their interest, while 2% agreed it definitely would not. 

Which DXP Vendors Offer Chatbot Integrations?

This is consistent with findings from the CMSWire 2025 Digital Experience Platforms (DXP) Market Guide. Some vendors are noted for offering chatbot functionality to help brands deliver fast digital customer experience.

For example:

• Acquia: Deploys an AI chatbot to assist with tasks throughout the asset lifecycle, like finding, summarizing, analyzing and understanding content.
• Coremedia: In August 2023, CoreMedia acquired Smarkio, a company producing chatbot and contact management software.
• HCL: Offers content management capabilities cover various content types, including text, graphics and other rich media, web content, mobile apps, chatbot and voice.
• Liferay: The headless layer of Liferay DXP, based on standards such as OpenAPI (REST) and GraphQL, makes it straightforward to expose data to other channels like mobile applications or chatbots, together with enterprise service bus and integration hubs when there’s a need to transform data.
• Squiz: The investment in RAG is also enabling a new capability called Conversation, allowing teams to deliver AI-powered chatbots and agents.
• Zesty.io: The integration of a generative AI chatbot into any organization’s website is designed to accelerate the search requests from users for the company’s products and services serving up information and pages immediately. Clients can train the chatbot using their own data to customize responses and functionality, ensuring the AI assistant meets their specific needs and preferences.

Service Cost and Operational Efficiency Rank Low as Primary Motivators

Reduced service costs were a primary goal for a large percentage of the audience, too. Twenty-eight percent said that this might impact their interest and 9% said it definitely did. Conversely, 4% said that chatbots' ability to reduce service costs might not be the driving force behind their interest and 2% said this was definitely not the case.

Consistent support quality, scalable service capacity and round-the-clock availability were low on the list of the primary goals that motivated interest in chatbots, with the latter garnering 0% interest. Just 3% said that consistent support quality was definitely a factor, followed by 8% who agreed it was not important and 1% who said it might impact them. 

Scalable service capacity was rated as being both definitely and an important factor (1% each), reinforcing the predominant focus on how chatbots improve customer experience — especially when speed and convenience matter most.

Which Chatbot Use Case Offers the Greatest Value for Your Team?

Product or service guidance offers some value for 89% of CX leaders’ teams 

One main use case of chatbots stands out as offering the most value:

For 89% of CX leaders in the US, chatbots are seen to offer their team some value for product or service guidance, which affirms this use case as the most widely recognized advantage. Of the remaining 11%, 8% cited exceptional value in loyalty program support, while just 2% felt chatbot use in order status updates added the most value, but this group was more definitive, saying this was the area where value was strongest for them.

These insights align with broader sentiments from a Tidio survey in which 60% of business owners believe AI chatbots can enhance the customer experience, and 32% of chatbot interactions relate to product availability, specifications and compatibility, further reinforcing that customers and businesses view product-focused support as the most impactful use of chatbot technology.

Further, the CMSWire 2025 CDP Market Guide emphasizes that purchase recommendations remain important. Most CDP platforms include some analytical capability and generally offer dashboard-style reports for tracking various key performance indicators (KPI) or for visualizing trends. Some CDPs also offer advanced predictive analytics that use ML techniques to enable analysis of customer behavior, which can be used to help determine most probable next-best actions that drive purchase recommendations, or even as a forecasting tool.

Chatbots for Simple and Complex Questions

A chatbot is a quick way to get a product recommendation, but when it comes to more complex questions, chatbots are not yet trustworthy — especially in the financial services sector, according to Marietta Allison, fractional customer experience principal at Sterling Hearted Consulting.

"The risk of a chatbot providing incorrect tax guidance, for example, is extremely high," said Allison, a former CX leader at Intuit. "Telling me what my account and routing numbers are for my checking account is easy."

Chatbots provide fast answers to easy questions (and deploying them quickly is a good thing). But the goal is to have a customer-facing chatbot that provides reliable answers to less standard, more complex questions.

Bridging Data Science and Support Teams

CX leaders can achieve this goal faster by connecting the data science teams who are building the AI algorithms powering chatbots with groups of support reps to partner together on data ingestion to avoid model hallucinations, according to Allison.

"I see many ways to do this," she said. "Have different groups of agents utilize a new chatbot model to create and edit responses to chat customers and use it to vet the accuracy of the model. Weight the value of agent-generated data based on tenure and other measurable agent attributes to have the most helpful and accurate chat responses prioritized, while responses from new agents are excluded or deprioritized in the model."

Validating Chatbot Responses

Further, have chat agents rank the accuracy of a chatbot-generated response with the fast click of a radio button, Allison added. When a chatbot response is validated by a threshold number of agents, move that response to the customer-facing chatbot model. "That way," Allison said, "you leverage your agents to fill data gaps in a model without causing an undue burden on them — and you get good info. out to customers as quickly as possible."

Building an Agent-Facing Chatbot First

Build an agent-facing chatbot first. Have your highly knowledgeable humans vetting the model responses in real time while you gain cost savings by improving your speed to proficiency for new agents, Allison said. "It can also improve customer loyalty and increase sales because when a new agent feels well supported, their confidence is passed along to the customer," Allison added.

What Is the Biggest Barrier to Wider Chatbot Adoption in Your Company?

32% of CX leaders agreed that data privacy concerns are the biggest barrier to wider chatbot adoption

Four predominant barriers are preventing the wider adoption of chatbots in companies:

 

Privacy and Budget Constraints Slow Progress

While California passed the California Consumer Privacy Act in 2018, followed by the Bolstering Online Transparency Act that mandates clear disclosures for companies using bot technology, only 17 other states have followed suit. However, other international laws, such as the European and UK GDPR, Canada’s PIPEDA, and Brazil’s LGPD, are also applicable to businesses that operate in these regions. It correlates, then, that 32% of US CX leaders cite data privacy concerns as the strongest barrier to greater chatbot adoption within their company. 

With the growing threat of fines, reputational damage and an ongoing increase in data breaches, many organizations are understandably cautious about implementing AI-driven tools that process sensitive customer information.

Budget constraints are also a barrier to entry and 22% of leaders agreed they're a stumbling block, while 16% agreed that limited internal expertise prevented more widespread adoption. 

The remaining 30% of the audience were neutral about whether customer acceptance was a barrier to wider chatbot adoption, reinforcing that while trust and transparency are top concerns, it’s often internal limitations like resources and readiness rather than customer resistance that slow the pace of adoption.

"Leverage your agents' knowledge," Allison said. It's the most untapped resource that companies have, according to Allison.

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Some of the major behavior changes leaders noted include a growing importance of online shopping (58%), higher expectations for customer service interactions (56%) and the increased importance of mobile experience (55%), according to the 2025 CMSWire State of the CMO Report. These shifts in customer behavior highlight the need for marketing teams to deliver seamless, personalized experiences across digital channels while demonstrating value and building trust. 

Which Vendor Trait Matters Most When Choosing a Chatbot Solution?

Flexible chatbot customization might be the most important vendor trait for 53% of CX leaders 

Clear trends emerge regarding chatbot solutions’ desired vendor traits:

Just over half (54%) of CX leaders agreed that flexible customization might be the most important vendor trait when they’re looking for a chatbot solution. Eight percent felt the same about easy platform integration, and another 8% about responsive customer care, while 5% agreed this was their priority regarding strong security standards. 

When it came to the trait that was definitely the most important, only 2% said flexible customization and 2% responsive customer care. 

There were also clear trends as to what traits were not prioritized. Seven percent felt flexible customization might not be the most important, 6% felt the same about easy platform integration, 3% about security standards and 1% about proven industry results. While flexible customization was the most important, there were also 2% who said this was definitely not the most important, followed by 3% who had the same attitude about responsive customer care. 

Customization Stands Out, but Preferences Remain Fragmented

The data suggests that while flexible customization is generally seen as the most important trait when selecting a chatbot vendor, no single feature stands out as definitively most important, highlighting a fragmented set of priorities among CX leaders.

Flexibility is highlighted in the CMSWire DXP Report. According to Sarah Kimmel, VP of research for CMSWire, "While the classic DXP was an existing integrated, monolithic environment consisting of both back office and presentation tiers, increasingly the idea of the composable DXP — a more modular, integrated ecosystem of services that work together cohesively — is coming into play."

Which Chatbot Success Metric Do You Monitor First?

52% of CX leaders always prioritize customer satisfaction scores

Three core metrics are used to measure :

 

CSAT Clearly Leads Over Operational KPIs

Zendesk’s 2025 CX Trends Report found that as many as 87% of businesses saw measurable CSAT improvements from using chatbots, and this success metric is the one US CX leaders have also prioritized. Fifty-two percent always monitored the CSAT and 22% did so sometimes. Only 4% said they never prioritized this metric.

Self-service containment was the other success metric that was monitored first. However, only 4% sometimes prioritized it and 3% usually did not consider it. Average handling time was also largely not a priority, with 16% who said they might believe or think it was worthwhile monitoring. 

This underscores how chatbots improve customer experience when designed to resolve inquiries efficiently and empathetically.

"Chatbots that know when a customer should be connected to an agent vs. just spitting out answers is also important," Allisons said. "I have many times had the experience where the chatbot just repeats the same stale, unhelpful or inaccurate information to my question, no matter how I reword it, and then be a blocker to me connecting to a live agent."

Related Article: AI and the Importance of Genuine CX Dialogues

Which Brand Voice Style Should Your Chatbot Reflect?

25% of CX leaders said their chatbot should always reflect an empathetic and caring brand voice

Two main preferred brand voices for chatbots emerged: 

 

Empathy vs. Energy: Brand Tone Is Split

Maintaining a consistent brand voice in the AI era is crucial to success, but opinions differ somewhat on the tone this voice should take. A quarter of CX leaders believe their chatbot’s brand voice style should always be empathetic and caring and another 25% say it should definitely be energetic and upbeat. 

"What if it was smart enough to adapt its tone to the situation and to that particular customer?" Allison asked.

However, whether this tone might be the former or the latter differs, with 18% choosing energetic and upbeat over 7% opting for empathetic and caring and another 10% saying this tone might not be suitable at all. A further 8% said they might want their chatbot to reflect a friendly and casual brand voice and 1% felt the same about the tone being professional and concise. The same percentage agreed they wanted an expert and authoritative tone. 

Four percent agreed that the tone should always be professional and concise and 3% shared the same sentiments for an expert and authoritative tone. While these percentages are lower, they are far more definitive than the 35% who only said the tone might align with one of the brand voice styles.

Which Data Source Best Trains an Effective Chatbot?

25% of CX leaders agreed that knowledge-based articles might be the best data source for training chatbots

Opinions differ on the best data sources for chatbot training:

 

Knowledge Articles Seen as Best Starting Point

As HubSpot’s Kolawole Samuel Adebayo stated, “AI chatbots, like human beings, are only as good as their training.” However, it’s evident from the audience analyzed, the opinions on the data sources used for this training vary. Using knowledge-based articles certainly attracts the most attention, with 25% agreeing it may be the best data source and 4% saying it is definitely the best. However, 43% said it might not be the best and 6% said it is definitely not so, revealing uncertainty and divided opinions on this data source.

Product documentation was the only other data source that drew opinions, as past chat logs and community forums did not register any interest. Just 1% said this documentation was definitely the best, while 16% said it might be. Four percent disagreed and said it might not be the best, which is less than 10% of those who felt the same about using knowledge-based articles.

"Starting with your knowledge-based articles is obvious, but don't end there," Allison said. "Most customers have already looked at your online information, and they are looking for more. At the risk of being a broken record, use your highly knowledgeable agents to create an ever-improving and expanding source of high-quality data to ingest. Agents know what is missing in the knowledge-based articles because they are the ones answering those customer questions."

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Which Chatbot System Integration is Your Top Priority?

Customer relationship platform chatbot integration is definitely the top priority for 33% CX leaders

Chatbot system integration is crucial to success across all platforms, with some taking priority:

 

CRM Integration Tops the Implementation Wishlist

Establishing and maintaining customer relationships are crucial to brand success, making it understandable why the majority of CX leaders in the US prioritize the integration of chatbots with their customer relationship platforms. Thirty-three percent said they definitely made this system integration a top priority, followed by 14% who said they did so sometimes. Yet, 7% said they usually did not prioritize this system integration and 9% said they definitely did not. 

Integration with marketing automation tools garnered a mix of opinions, with 18% who said they might put these systems at the top of their list, 10% who said they definitely would and 4% who said they might not. Order management software integration was also not a priority, with 1% saying they might not prioritize this integration and 1% agreeing they might. The same percentage concurred about knowledge management hub integration. 

These statistics suggest there’s a focused but uneven approach to chatbot integration across key business functions, but that, once again, customer experience and relationship are crucial.

"I would think (order management software) would actually be a quick win for customers and for reducing contact center volume," Allison said. "Order management would be a highly accurate low hanging fruit of chatbot response data."

How Would You Like to Collect Feedback on Chatbot Interactions?

63% CX leaders might like in-app prompts for collecting chatbot interaction feedback 

Opinions on collecting feedback for chatbot interactions vary somewhat:

 

In-App Prompts Win as the Feedback Favorite

In a 2024 Consumer Reports Survey, a third of Americans said they had used an AI chatbot in the past three months. These interactions record a vast amount of data, and for CX leaders, this feedback can be incredibly valuable in shaping future experiences. 

However, preferences for how this data is collected differ, with the majority (63%) saying they might like in-app prompts compared to the 11% who might prefer other methods. Twenty-one percent might like follow-up phone calls, 1% might not prefer this method, and 4% agreed that open comment fields might not be the best option. With the audience largely preferring in-app prompts, indications are that real-time, contextually relevant feedback mechanisms are the most effective way to capture customer sentiment. 

"It would make sense to use in-app responses to target areas for more model training," Allison said. "Use customer feedback to automatically make your model better."

Which Statement Best Describes Your Current Chatbot Deployment Stage?

31% of CX leaders are somewhat successfully rolling out chatbot deployment 

Chatbot deployment stages indicated current adoption trends:

 

Looking at the current stages of deployment, it’s immediately evident that of the 396,226 CX leaders, few have successfully rolled out chatbots. This is somewhat alarming, as a Glassix study shows that AI chatbots enhance conversions by 23%. Of the audience, only 4% were definitely successfully rolling out chatbots to teams, 31% were somewhat successfully doing so, 11% were somewhat struggling and 4% were definitely struggling.

Twenty percent thought that optimizing performance was important for the rollout, 3% definitely believe this is crucial and 1% thought it may not be the best focus. Those who could describe their rollout as resulting in a fully mature program numbered only 5% who said their program was mostly mature, while 9% said their program was not mature at all and 8% said it was somewhat immature. 

Two percent said that definitely exploring their options was essential, indicating they had not yet begun a rollout, while 1% somewhat believed they were essential. Only 1% were somewhat successfully running a pilot, proving that there’s still a large gap between interest in AI chatbot adoption and actual implementation maturity.  

Which Advanced Chatbot Capability Would Add the Most Future Value?

20% of CX leaders agreed that multilingual chatbot support would add significant future value

It’s evident which advanced chatbot capabilities are most desirable:

 

Chatbots are already revolutionizing customer experience, but they have the potential to do even more in the future. For CX leaders, the advanced capabilities that would add the most value in the future are split into five categories, with multilingual support leading the way. Twenty percent said this type of support would definitely add significant future value and 16% said it might add some value, while only 1% agreed it might not add much value in the future.

Sentiment-based responses would definitely add significant future value for 8% and 18% said it might add some future value to CX. However, 4% said these responses would definitely not add much value and 2% said they might not. Proactive engagement prompts came in third, with 12% saying this might add some value and 4% saying it definitely would. However, another 4% agreed this might not add much future value, creating a distinct zeroing in value. 

Visual media handling and predictive intent routing are fourth and fifth, respectively, with the former definitely adding future value for 2%, while 2% agreed it might add some CX value and 2% said it might not. For the latter, 1% said it would definitely add future value and 2% said it might. 

The overall trend in opinions here reflects that CX leaders are prioritizing tools that deepen emotional connection and global accessibility, reflecting a shift away from novelty toward meaningful, human-centric experiences at scale.

Related Article: AI in Customer Experience: Powerful Use Cases You Shouldn’t Ignore

How Should a Chatbot Transfer Conversations to Human Agents?

49% of CX leaders agree chatbots should always transfer conversations to a human if the query cannot be matched to a known intent

Despite chatbots' proficiency, there are two predominant cases when human agents need to step in:

 

If a chatbot cannot understand a user's goal or request, human intervention is required, and 49% of CX leaders believe this is the point when a conversation should definitely be transferred to a human support agent. Another 22% agreed that the transfer should always take place at key moments and 29% said this might be the right time to transfer. 

With nearly half the audience opting for escalation after intent check, the importance of having a seamless, well-timed handoff to human agents becomes clear, ensuring that customers receive accurate support when automation reaches its limits and preserving trust in the overall experience.

As an example from a provider, CoreMedia reported in the CMSWire 2025 DXP Market Guide that it values AI-powered automation these ways:

• Content integrity: Ensuring content accuracy and adherence to brand and governance, including GDPR
• Intelligent automation: Automating more low-level tasks related to the content management process
• Human + AI team: Having an intelligent assistant to enhance the composable content process and related creativity

On Which Channel Do You See The Greatest Chatbot Impact?

25% of CX leaders somewhat believe mobile apps have the greatest chatbot impact 

Chatbot impact varies across channels, with some more effective than others:

Mobile applications are by far the channel on which CX leaders see the most impact from chatbots, with 14% saying they definitely believe this channel has the greatest chatbot impact, followed by 25% who somewhat believe so. Eleven percent disagreed, though, saying that they somewhat believe mobile applications do not have the greatest impact. 

SMS or text support follows, with 21% who think this is where chatbots make the most impact. Thereafter, 8% definitely believe social media messaging has the greatest chatbot impact, and 8% somewhat believe the same, while 1% somewhat think it has limited impact. 

Notably, 14% somewhat believe a company website has the greatest chatbot impact, despite this being most customers’ major touchpoint. However, research shows that the global chatbot market size was valued at $7.76 billion in 2024 and the mobile applications segment accounted for the highest revenue share. This aligns with the leaders who found this was the channel where they see the most impact. 

Which Chatbot Personalization Feature Would Improve Customer Satisfaction the Most?

24% of CX leaders said that real-time chatbot product tips would definitely significantly improve customer satisfaction 

Preferred chatbot personalization features for enhancing customer service are split into four categories:

 

Personalization has become integral to marketing and CX, with McKinsey revealing that 71% of consumers expect personalized interactions and 76% feel frustrated when they don't receive them. Chatbots play an integral role in personalization, and there are some features that CX leaders believe would improve customer satisfaction levels even further. 

The most desired feature was real-time product tips, which 24% said would definitely significantly improve customer satisfaction and 12% said might improve it. Conversely, 9% said this feature might not be the most effective, which is likely due to the context the chatbot is used.

Location-aware answers were next, with 4% agreeing they would definitely significantly improve CX and 40% saying they might improve it, versus 9% who said these answers might not have a major impact. Contextual greetings were cited as the personalization feature that might improve CX by 1% and another 1% said that adaptive tone of voice would definitely significantly improve and might significantly improve CX. These lower numbers highlight that CX leaders’ focus is currently on broader, functional personalization features like language support and emotional intelligence, rather than on nuanced or stylistic enhancements. 

Which Region Best Describes Where Your Company is Based?

39% of US CX leaders are likely based in the West 

CX leaders’ company distribution varies dramatically across the US:

 

With 16% of CX leaders definitely based in the West, 23% may be based there and just 5% who might not be based there, the largest percentage of the audience’s companies seem to operate from this region. This is understandable, as the West is the leading business hub in the US and it’s home to Silicon Valley, Los Angeles and Seattle. California alone also ranks as the world’s fourth-largest economy. 

The Midwest is popular too, with 48% saying their companies may be based there, while the Southwest is at the bottom with 7% saying they might be based there. This vast difference shows where entrepreneurs flock to and which regions in the US drive innovation, attract investment and shape the future of customer experience.

What’s Next for Chatbots in Customer Experience?

These statistics clearly show that as chatbot adoption matures, CX leaders are becoming more intentional about where and how this technology fits into the customer journey. Their opinions signal a clear shift from experimentation to optimization, where the focus is on long-term value, meaningful integration and maintaining a human-centered brand voice. 

Looking ahead, the industry looks set to elevate chatbot experiences beyond simply convenience, making them an integral part of personalized, emotionally intelligent customer service strategies that scale.

Methodology

Sourced using Artios from an independent sample of 396,226 United States CX leaders' opinions across X, Reddit, TikTok, LinkedIn, Threads and BlueSky. Responses are collected within a 95% confidence interval and 3% margin of error. Results are derived from opinions expressed online, not actual questions answered by people in the sample.

About the representative sample:

• 54% of United States CX leaders are between the ages of 35 and 64.

• 60% identify as male and 40% as female.

• 40% earn between $200,000 and $500,000 annually.