B2B Companies Using AI in Marketing and Sales (2025)
Draft B2B strategy and ad copy, then use cited findings to define a measurable pilot.
Mdz.ai editorial · Reviewed Sep. 29, 2026
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What the evidence says about B2B AI adoption
The figures below distinguish a 2025 publication citing a 2024 B2B survey, a 2025 global AI survey, and separate 2026 B2B and sales findings. They describe survey responses, not guaranteed results for a specific company.
19% + 23%
B2B gen AI adoption stages
A McKinsey article published in 2025 reported that 19% of respondents were implementing gen AI for B2B buying and selling, while another 23% were in the process. Its footnote dates the survey to April 3–24, 2024 (3,942 decision-makers across 13 countries), so treat these as 2024 survey results.
McKinsey article, March 2025; survey fielded April 202467%
Reported revenue increase
In McKinsey’s 2025 global AI survey, 67% of respondents whose organizations used AI in marketing and sales reported some business-unit revenue increase in the prior 12 months. This is self-reported association, not proof that AI caused the change.
McKinsey Global Survey, fielded June–July 20254.8 hours · 72%
A 2026 sales follow-up
Gartner reported 4.8 hours saved per seller each week on average, while 72% of sales organizations reported low reinvestment of that time in high-value activities.
Gartner survey, January–February 2026Current B2B adoption context
McKinsey’s 2026 Global B2B Pulse reports that 22% of organizations had fully implemented gen AI capabilities and another 31% were actively adopting them. The survey covered nearly 4,000 decision-makers across 13 countries; its definitions and population should not be treated as a direct comparison with the earlier survey.
McKinsey 2026 Global B2B Pulse, May 28, 2026A reported B2B deployment example
McKinsey describes an industrial materials distributor that used AI to rank opportunities and gen AI to research public project data and personalize outreach. The company reported more than $1 billion in new opportunities, a 10% pipeline increase, and over twice the click-through rate in its first fiscal year. This is a publisher-reported case, not a controlled estimate or promised outcome.
McKinsey B2B deployment case studyA Practical AI Workflow
An illustrative process, not a measured performance benchmark.
Turn the evidence into a measurable pilot
These are practical starting points, not claims that AI will improve each metric. Set a baseline and a quality threshold before enabling automation.
| Workflow to test | Compare against baseline | Keep a human in control of |
|---|---|---|
| Marketing research and first drafts | Time to approved draft, factual corrections, rework | Claims, audience fit, brand and legal review |
| Sales call summaries and CRM updates | Minutes saved, correction rate, missing fields | Customer commitments and final CRM record |
| Lead research and next-best action | Research time, accepted recommendations, qualified progression | Source verification, prioritization, customer contact |
| Outbound message variants | Qualified replies, opt-outs, complaints, cost per qualified response | Consent, personalization facts, send approval |
Evidence, boundaries, and operating risks
What these surveys can support
- AI use is reported in B2B buying and selling, but the cited 2025 B2B survey also shows many respondents were not yet implementing it.
- Reported business outcomes vary; 2025 McKinsey results are self-reported and do not isolate causal lift.
- The Gartner seller-time result is from 2026 and should not be presented as a 2025 benchmark.
Risks and practical controls
- Incorrect claims: require evidence links and human approval before publishing.
- Data exposure: use approved, minimized inputs; check the provider’s retention and training terms before sharing business data.
- Cost without impact: track usage, review time, rework, and business outcomes together; stop a pilot that misses its threshold.
- Workflow mismatch: keep AI advisory until the team proves accuracy and has a rollback path.
Sources and method
- McKinsey, “Unlocking profitable B2B growth through gen AI”, published March 27, 2025. Its footnote identifies the underlying survey as fielded April 3–24, 2024, with 3,942 B2B decision-makers across 34 sectors, eight major industries, and 13 countries. The publication date is not the survey date.
- McKinsey, “The state of AI in 2025”, 1,993 participants in 105 nations, fielded June 25–July 29, 2025. The revenue question was asked of respondents whose organizations used AI in the relevant function; results are self-reported.
- McKinsey, “The surprising economics of B2B growth”, published May 28, 2026; 2026 Global B2B Pulse of nearly 4,000 decision-makers across 13 countries.
- Gartner, “AI saves sellers nearly five hours per week…”, published May 19, 2026; survey of 210 CSOs and senior sales leaders, fielded January–February 2026.
Reviewed September 29, 2026. Survey populations, questions, and periods differ; do not compare these figures as a time series or treat them as a forecast for an individual company.
Use the evidence to plan a B2B AI pilot
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- 3Step 3
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FAQ - B2B AI Adoption
Common questions about using AI for B2B marketing and sales
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