What’s the return-on-investment (ROI) for AI in account-based marketing (ABM)? Turns out, that’s a hard question to answer: Inflexion Group’s 2025 AI in ABM Benchmarking Study found 58% of account-based marketing (ABM) teams aren’t measuring AI return-on-investment (ROI).
Why? It’s not technology adoption. The challenge is timing. Our study found nearly 40% of ABM teams say it’s too early to measure AI’s impact. This is also the likely reason our benchmark found only 6% report good or strong ROI from AI in ABM.
That doesn’t mean ABM-ers see no benefits from AI adoption, and it doesn’t mean teams can consider themselves excused from measuring ROI. Inflexion Group’s benchmarking study points to three opportunities for ABM teams to address before lack of ROI reporting dampens AI enthusiasm and shrinks budgets.
- Opportunity 1: Report on leading indicators of AI impact to show incremental progress towards ROI for ABM
- Opportunity 2: Monitor financial impact to build patience and put progress in context of key business goals
- Opportunity 3: Track customer-centric ROI metrics to avoid the trap of internal-only perspectives
Note: This is the fifth article in our series built around our 2025 AI in ABM Benchmarking Study. Dorothea Gosling shared highlights of what we found out about the benefits and business impact teams are seeing from their AI deployments in the first post in the series. In this post, I’m offering more of our data on benefits and ROI, plus guidance for building a better reporting foundation to measure them.
Benefits of AI in ABM so far: better insights, personalisation and productivity, but not revenue (yet)
Source: Inflexion Group 2025 AI in ABM Benchmarking Study
Opportunity 1: Report on leading indicators of AI impact to show incremental progress towards ROI for ABM
When it comes to ROI reporting, “too soon to tell” is the prevailing sentiment in the study. Nearly 40% of respondents said they felt it’s too early to measure the impact AI is having. This highlights another finding, which is that 53% of companies have been using AI for ABM for less than one year, and 43% of companies consider themselves to be experimenting with it today. (Read more about what our study found about AI adoption in this post.)
Not tracking AI ROI may be the biggest risk of all for ABM teams
Source: Inflexion Group 2025 AI in ABM Benchmarking Study
This points us to an even bigger danger for ABM teams: 58% aren’t measuring ROI on AI at all today. For those who are seeing ROI impact, for now, it’s modest. Just 6% term describe what the ROI of AI as “good (2%),” “great (2%)” or “transformational (2%).” Another 16% said their ROI from AI was modest, about a 1.5X to 2X return.
ROI on AI is modest so far and reported by fewer then 10% of ABM teams
Source: Inflexion Group 2025 AI in ABM Benchmarking Study
The risk here can’t be overstated: While actual measurement of ROI is low, expectations are high for AI in ABM to deliver great things. Any reasonable gap between AI investment and expected financial impact won’t last. In 2026, critical mass of ABM-ers enter their second year of AI deployment. Even for longer B2B sales cycles, it will be possible to see AI’s impact across multiple financial measures, including revenue and pipeline. Marketing teams must begin measuring ROI now, starting with credible and predictive leading indicators.
Leading indicators are outputs or outcomes that show up long before closed deals, making them the first area where AI benefits (or problems) start to show. Based on the benchmark results, a good place to start is insights, a foundational component of ABM delivery that is also an ideal use case for AI.
The Inflexion Group study shows significant early positive impact from the use of AI for insights gathering and quality improvement:
- Insight quality: 96% of respondents said AI delivers better account intelligence depth and quality and 56% said this was a significant benefit.
- Better reporting: 75% of benchmark respondents, AI delivers better data insight and reporting.
ABM-ers can now gather the insights they need for more effective engagement faster and at scale. Using AI for scaled account insights expands potential to deploy ABM programs to a larger group of accounts without sacrificing quality or demanding more resources. This is directly related to many company’s goals to reduce customer acquisition cost (CAC).
Leading indicators are also important because they track where AI becoming embedded in typical ABM processes. Respondents were enthusiastic about AI’s impact on ABM processes, including time savings and productivity gains for the team, and even team satisfaction and development.
- Productivity: For 84% of respondents, AI is delivering productivity gains in core ABM activities
- Time savings: 93% report time savings for their teams
- Team development: 83% said investments in AI are benefitting team satisfaction and development
All of these are early positive signs of change but be careful about reporting on them in isolation. Make a clear (ideally visual) link between leading indicators and the financial or other business key performance indicators (KPIs) so anyone reviewing ABM reporting can see progress towards the company’s most important goals.
Opportunity 2: Monitor financial impact to build patience and put progress in context
Once we look beyond early internal indicators like insights productivity gains, impact gets more elusive. While relatively high percentages of respondents said they saw benefit from areas like competitive advantages and even sales and marketing alignment, significant percentages said they weren’t yet experiencing positive effects in critical areas connected to overall company business impact.
What does that look like across key financial goals?
- Pipeline increase: For 37%, AI is delivering some benefit (32%) or significant benefit (5%) on increased pipeline, while 45% reported no change.
- Pipeline velocity: While 27% saw benefit from increased pipeline velocity, 41% reported no change.
- Revenue increase: Just 26% reported increased revenue from AI deployments in ABM, and nearly half (46%) said they’re not seeing a revenue change yet.
- Profitability and customer acquisition cost (CAC): Results here are mixed, with 48% reporting some or significant cost reduction, but another 40% showing no change and even 5% reporting significant negative impact on costs. Cost reduction is a clearer demonstration of the positive impact of productivity improvement on overall profitability and CAC reduction.
Productivity and scaled insights get high marks, but companies also sound a cautionary note around cost and revenue impact so far
Source: Inflexion Group 2025 AI in ABM Benchmarking Study
Even though results are limited for financial impact so far, ABM teams need to keep an eye on these as 2026 progresses. Marketing will be under increased scrutiny to demonstrate revenue impact from AI deployments. Teams who make it easier for executives to see a direct link from where AI is being applied to key business goals are more likely to be given time for programs to achieve that financial impact.
Opportunity 3: Track customer-centric ROI metrics to avoid the trap of internal-only perspectives
Why might teams be reporting limited, or even negative, value for cost reduction, engagement rates, pipeline and revenue? Again, timing is clearly part of the challenge, but not the full story. As teams deploy AI into general demand creation, we’re experiencing a collective up-levelling of B2B outbound outreach, both marketing- and sales-led. What were best practices are now standard operating procedures, so it’s harder to stand out compared to peers. At the same time, scaling use of ABM-like practices to a larger share of accounts can lead to more costs.
For AI investments to deliver revenue impact, ABM teams need to understand what’s working with customers and prospects. Companies are grappling with rapid changes in their buyer’s journey. Not having an accurate, up-to-date view into how decisions are made around purchase, expansion, and renewal this slows ROI realization.
Top-ranked impact areas drop off quickly when teams look beyond internal measures
Source: Inflexion Group 2025 AI in ABM Benchmarking Study
Why does this slow ROI? Our study suggests most teams are focused on optimizing internal processes that may no longer be relevant. (Read more about the issues of solving today’s problems with tomorrow’s technology in this post). This shows up most clearly based on one leading indicator that was notably missing for many companies: engagement.
Just 18% of ABM-ers said they’re tracking improvement in engagement rates from their AI use. This is the first place we’d expect to see improvement if AI deployment is effective, and where we’ll find out what’s not landing well with our buyers. Related to this are improved targeting accuracy (2% saw this benefit from AI) and enhanced personalization capabilities (11%). Using AI to improve these areas should result in higher engagement. Only by tracking engagement can we tell if perceived improvements are having the desired effect with our target audiences.
Why are customer-focused metrics like engagement and competitive advantages so valuable, especially early in new technology adoption cycles like we’re experiencing with AI? Buyers often adopt new tools and approaches faster than sellers do. ABM teams using AI to perform outdated tasks more efficiently won’t deliver revenue impact, and internal productivity metrics won’t show where this is happening. It also won’t show where peers are outperforming your company.
Customer-focused metrics are essential to complete ROI tracking. Companies who don’t use AI and other resources to update data, processes and other foundational areas limit potential benefits from AI. (Read more about the barriers to AI adoption in this post.) We encourage ABMers to include these, starting with engagement, competitive comparisons, and relationship strength measures.These are also areas leadership will value more than productivity improvements, especially if cost savings aren’t there yet.
As AI for ABM is early in its investment cycle for most companies, there is time to update reporting to include ROI and more customer-centric metrics. ABM-ers can work with their marketing, sales and revenue operations partners to define additions to regular reporting that track near-, mid- and long-term ROI indicators.
Work with marketing leaders to ensure the chosen metrics will answer the kinds of questions executives outside of marketing are likely to have about how AI investments are impacting key company objectives. While most of those are likely to be about revenue and profitable growth, be sure to find out about any others related to productivity, customer relationships, or other focus areas as well.
What’s next: When it comes to ROI, stay on the journey, but with a better guide
Remember the interminable car rides when we were kids, where it felt like forever to get where we were going? It turns out the business impact of AI for account-based marketing feels slow to arrive, but we’re just at the start of a longer journey. Patience is hard to maintain when you’ve been promised what’s at the end of the trip is going to be great. With AI, we hear lots about good outcomes, but we can’t yet see the end of the road for ourselves.
Where does that leave account-based marketers, who are happy to invest in AI, but have yet to show revenue impact? Just like those long car trips, it’s taking time for AI to deliver on its full promise in ABM, but our study shows companies expect the view at trip’s end to be worth it. Next week, Dorothea Gosling will share insights on what to expect from AI in ABM for 2026 and beyond.
Want more insights from the 2025 Inflexion Group AI in ABM Benchmarking Study?
ICYMI: The whole series on our benchmarking report to date
About the 2025 AI in ABM Benchmarking Study
The 2025 Inflexion Group AI in ABM benchmarking study looks at how ABM professionals are integrating artificial intelligence (traditional, generative and agentic) into their daily workflows, and whether those efforts are creating measurable business value. It included two phases of research. The first was 20 in-depth interviews with global ABM programme leaders during August and September 2025. The second was a quantitative study in partnership with B2B Marketing where we invited ABM-ers to complete an online survey during September and October. A total of 66 people participated. Just over 50% of respondents were from global, enterprise-level companies with more than 5,000 employees and the rest were from companies ranging from those with fewer than 200 employees (23%) and from 201 to 1,001 employees (26%).
