Despite predictions that AI would be standard in CRM by 2025, new research from Workbooks suggests AI adoption is still lagging inside many CRM systems — especially in the mid-market. The company believes the AI adoption gap inside CRM systems is set to close rapidly in 2026.”
However, the prediction wasn’t wrong — adoption has simply taken longer than expected. Industry reports still suggest generative AI will reshape how application leaders transform their CRM and customer experience (CX) operations. Workbooks argues the mid-market is where that shift has been slowest — and where it’s about to accelerate.
CRM users will spend less time on manual updates, AI will improve coordination across customer interactions, and productivity will become the new battleground. To that end, Workbooks’ December launch of an AI-enabled CRM aims to help bring AI into day-to-day CRM workflows.
AI-enabled CRM can automate repetitive sales tasks, improve data accuracy, and empower sales teams to work smarter. The launch coincides with Workbooks' latest study, which shows a significant disparity between AI use in business and its adoption in CRM in both the U.S. and the U.K.
"The new era of CRM is here. AI will define the next generation of customer engagement: more predictive, more personalized, and ultimately, more profitable," said Workbooks CEO John Cheney.
Mid-Market CRM Faces an AI Bottleneck
According to Cheney, Gartner was correct about AI's adoption into CRM, but did not account for the mid-market bottleneck along the journey. Workbooks' research shows AI is already transforming productivity for early adopters.
"But the majority are still stuck, constrained by a lack of expertise and rigid, legacy CRM systems that simply aren’t built for the AI era. The most successful firms use their CRM to empower teams to build meaningful connections, not just track metrics," he offered.
Cheney attributed the stagnation in adoption to three factors. He sees the most significant barrier as a lack of internal expertise, along with substantial technical constraints and the concern that incorrect AI outputs could appear in critical opportunity records.
"While AI adoption is widespread at a leadership level, CRM remains a particularly sensitive area because it sits at the heart of revenue, forecasting, and customer relationships," he told CRM Buyer.
Highlighting Global Implications for Closing the Gap
The results of the Workbooks study focus on the U.S. and U.K. markets. While research originated in the U.K., Workbooks has a significant and growing presence in North America. Comparative data from its 2023 and 2024 surveys show several universal trends.
According to Workbooks’ researchers, the findings highlight the market potential for AI-enabled CRM:
- Only 16% of mid-market firms in the U.K. currently use AI in their CRM, despite 90% using AI elsewhere.
- 59% of sales and marketing leaders in the U.K. plan to significantly increase AI adoption next year.
- 23% of CRM users in the U.S. have adopted AI in their CRM, while 93% of U.S. leaders use AI daily.
- 66% of CRM users in the U.S. plan to ramp up AI in CRM this year.
Early adopters in both markets report high productivity gains, particularly in reporting, analytics, and operational efficiency. Companies using multiple AI features see scores approaching “substantial impact” compared to those using just one tool.
Cheney sees 2026 as a tipping point for more rapid adoption of AI in CRM systems. Over the next year, AI will become more reliable, more affordable, and more embedded in everyday CRM workflows.
"At the same time, leaders are demanding clear ROI rather than experimentation, and sales teams expect CRM systems to guide them actively," he said. These shifts will accelerate adoption and move CRM from a system of record to a system of action in 2026.
Workbooks Targets the Mid-Market With Agents
Workbooks’ AI-enabled CRM addresses these challenges, offering seamless integration, actionable insights, and tools that scale with a team’s needs, Cheney noted. It is built for teams without specialist resources.
That design lowers the barrier to adoption compared to competitors’ enterprise-level AI offerings, such as Salesforce or Microsoft. Instead of complex AI frameworks, it offers ready-made agents that work out of the box.
Core tools like Scribe deliver immediate value with minimal setup, while advanced agents only require simple, plain-English configuration. As a result, AI becomes accessible without the cost or complexity of enterprise platforms, he explained.
"Sales Coach is tailored using straightforward inputs that reflect how a business actually sells. Custom CRM records capture value propositions, case studies, and common objections, allowing the AI to recommend relevant strategies based on each company’s unique sales process rather than generic sales models," Cheney said.
Key Agents Focus on Scoring and Data Trust
Workbooks argues that several common CRM gaps make this release timely.
Users have complete control over how the Research Agent scores prospects against an Ideal Customer Profile. ICP scoring can use multiple criteria, with each factor weighted according to what matters most to the business.
Research Agent can also search for specific types of news or particular sources. It ensures accurate company background information by drawing from sources such as the prospect’s website, Companies House, and Endole.
Sales Hygiene compares multiple evidence sources, such as emails, meeting summaries, and existing CRM records, to flag inconsistencies. It suggests updates but never commits changes automatically, keeping users in complete control of the record.
Why It Doesn’t Layer Onto Existing CRMs
Workbooks AI cannot layer onto existing infrastructure for businesses not yet ready for a total overhaul. It operates natively within the Workbooks CRM platform.
"AI agents currently work on data held within Workbooks CRM and through controlled web searches. Integrations with tools such as Microsoft Teams and Zoom are supported via the Scribe agent, with transcriptions and summaries written back into the CRM," Cheney explained.
But future phases will provide an alternative adoption plan. Workbooks plans to leverage the model context protocol (MCP) to support secure external queries of Workbooks AI from other systems.
"This phased approach maintains data quality and trust while enabling broader interaction over time," he said.
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