In enterprise partnerships and business development, tools change every few years; the fundamentals — trust, timing, and judgment about what a relationship actually needs — don’t. AI is the newest tool, and the data on how it’s being used shows a field still sorting out the difference between adopting it and actually benefiting from it.
Adoption is happening; effective use isn’t, yet
AI usage among sales reps rose from 24% in 2023 to 43% in 2024, and 56% of sales professionals now report using AI daily. Daily users are twice as likely to exceed their sales targets than non-users, and sellers who effectively partner with AI tools are, according to Gartner research, 3.7 times more likely to meet quota than those who don’t. Those are strong numbers for AI’s upside in BD — but they sit next to a much less flattering one: only 19% of sales reps use the AI features built directly into their own sales tools. Most of the rest are copy-pasting prompts into general-purpose chatbots, a workflow that misses the CRM context, account history, and signal intelligence that purpose-built tools are designed to surface.
Where AI genuinely multiplies BD work
The clearest wins cluster around the unglamorous parts of the job: account research, first-draft outreach, meeting-prep synthesis, and follow-up cadence. Reps report saving one to five hours a week on this category of task, and Bain’s 2025 research suggests AI could roughly double active selling time by eliminating this kind of routine load. In a partnership context specifically, that means more time for the parts of the job AI can’t do — reading a stakeholder room, sensing when a partner’s enthusiasm has quietly cooled, deciding when to push a renewal conversation earlier than the calendar suggests.
Where it doesn’t, and shouldn’t
Partnership governance, sponsor trust, and renewal judgment are not tasks to hand to AI, and treating them as such is the fastest way to convert a productivity tool into a credibility problem. A partner can tell the difference between a personalized message and a well-disguised template; the erosion of trust that follows doesn’t show up in an activity dashboard, which is exactly why it gets missed until a relationship has already gone cold.
| AI-suited work | Judgment-required work |
|---|---|
| Account and market research | Reading stakeholder sentiment and sponsor trust |
| First-draft outreach and follow-up cadence | Deciding when to move a renewal conversation earlier |
| Meeting-prep synthesis and CRM hygiene | Negotiating terms and resolving partner conflict |
Frequently asked questions
Should a BD team standardize on one AI tool or let reps choose? The data favors standardizing on tools embedded in the CRM and sales stack rather than leaving reps to default to general-purpose chatbots — embedded tools carry account context that generic tools don’t, and the adoption gap (43% overall usage versus 19% using embedded features) is exactly where value is being left on the table.
Does using AI in outreach reduce authenticity with partners? Only if it’s used to replace judgment rather than free up time for it. AI-assisted drafting used to speed up research and first drafts, then reviewed and personalized by a human before it reaches a partner, preserves authenticity; AI output sent unreviewed does not.
Takeaways
- AI adoption in sales and BD has nearly doubled in a year, but most of that usage bypasses the embedded tools built to use account context well.
- The highest-leverage use of AI in partnerships is reclaiming time from research and drafting, not replacing relationship judgment.
- Governance, sponsor trust, and renewal timing remain human-judgment work — treat them that way deliberately, not by default.
- Standardize on embedded, context-aware AI tools rather than leaving reps to improvise with generic chatbots.