Research from Salesforce, McKinsey, and Boston Consulting Group highlights how AI is creating value in the work surrounding customer engagement. Growth executive Muge “Emma” Cody examines where the AI tools earn their place and where experience and judgement remain essential.
Ask Muge “Emma” Cody where AI is helping business development teams most, and she starts with something less glamorous than the technology itself: time.
Look at the calendar of anyone responsible for bringing in new business and the pattern is familiar. Research before a first meeting, notes after it, a proposal draft due Friday, a pipeline review on clean data. The conversations that move a deal forward fit into whatever time is left.
For Cody, a growth executive and strategist, the true measure of AI is not how much work it can perform, but how much time it frees up for experienced professionals to focus on the work only they can do.
The Hours Around The Conversation
Salesforce’s seventh “State of Sales” report (2026), based on a survey of 4,050 sales professionals, found that sellers spend about 40 percent of their time selling. The other 60 percent goes to activities such as administrative work, planning, and preparation. Most of the week still goes to non-selling work.
McKinsey has documented what happens when some of that time comes back. In “Unlocking Profitable B2B Growth Through Gen AI,” the firm describes a company whose sellers spent only 20 percent of their time with customers, compared with a third to half at successful Business-to-Business (B2B) sales teams. A combination of generative AI and other automation freed up more than 10 percent of the allocated time of the sellers.
McKinsey’s May 2026 report, “The Surprising Economics of B2B Growth: The New Survival Threshold, and What It Takes to Thrive,” drawing on its “Global B2B Pulse Survey,” found that 22 percent of organizations had fully implemented generative AI capabilities, while another 31 percent were actively adopting the technology.
The Returns Are Starting to Show
The distinction between using AI and realizing value from it is becoming clearer.
McKinsey’s 2026 B2B research found that among market leaders embedding AI into commercial workflows, 59 percent cited efficiency as a primary benefit and 53 percent cited improved customer experience.
In “The Future of B2B Sales: How Growth Champions Rewire Their Playbooks with AI” (July 2026), McKinsey further examined how leading organizations are moving beyond isolated tools and redesigning commercial workflows around customer needs, opportunity management, pricing, and sales execution.
Boston Consulting Group’s “Applied AI Index 2026,” released in September, found that nearly half of surveyed companies were generating value from AI. Of those, 7.5 percent qualified as “future-built,” BCG’s most advanced category, while another 41 percent were scaling AI and realizing some value.
Future-built companies reported 2.4 times the revenue growth of laggards. The findings, based on a survey of 1,330 executives and senior leaders, show an association between AI maturity and business performance, not proof of causation. They also cover AI across the enterprise, rather than business development specifically.
For Cody, the findings are encouraging. The question is no longer whether AI belongs in business development. It is where.
Four Places AI Is Earning Its Keep
McKinsey’s July 2026 research identifies several commercial activities where AI can improve productivity and execution. For Cody, four applications stand out as particularly valuable to business development teams.
- Customer Intelligence. AI can consolidate annual reports, market developments, customer priorities, competitive information, and previous interactions into a starting brief. The executive still validates the information and interprets its significance, but spends less time gathering it and more time preparing for a substantive customer conversation.
- Opportunity Prioritization. AI can analyze account characteristics, documented strategy, buying signals, historical performance, and pipeline activity to help teams identify opportunities deserving greater attention. The value lies not simply in scoring opportunities, but in helping leaders direct limited resources toward the most promising pursuits.
- Proposal Development. AI can accelerate first drafts of proposals using approved content, previous responses, and established requirements. Teams can then concentrate on solution differentiation, pricing, compliance, and the specific customer problem they are trying to solve.
- Pipeline Discipline. Automated meeting summaries, follow-up actions, and CRM updates can reduce administrative work while improving the completeness and timeliness of pipeline information. With appropriate review and validation, that creates a stronger foundation for forecasts and management decisions.
None of these replace the person doing the work. Each one gives time back to them.
Experience Still Makes The Call
AI can help assess which opportunities are worth pursuing, but it cannot replace the judgment behind the final decision. It may miss when a customer’s stated requirement masks a deeper concern. And it cannot build the trust that carries a relationship through a difficult negotiation or delayed delivery.
Those are the moments when skilled business development professionals make the difference. Cody sees AI as a way to give them more time for that work. The teams that benefit most, in her view, use the technology to strengthen their people’s judgment, not replace it.
BCG’s research points to the importance of workforce development alongside AI adoption. Leading organizations are investing in employee training and redesigning roles to integrate AI into how people work, rather than treating the technology solely as a means of reducing headcount.
Measure AI Like Any Growth Investment
The case for AI ultimately has to survive financial scrutiny.
McKinsey’s State of AI in 2026: On the Road to ROI (August 2026) found that 80 percent of respondents reported improvements in individual productivity. Yet only 37 percent said AI had made a positive contribution to their organization’s earnings before interest and taxes (EBIT).
That gap matters. Individual productivity gains do not automatically translate into enterprise financial results.
BCG’s “The Formula for Agentic AI Value” similarly found that 95 percent of future-built companies measured AI through the Profit & Loss (P&L) or proxies such as Key Performance Indicators. Companies that track AI directly in their P&L statements reported three times the AI value of those without formal measurement, 3.6 percent versus 1.2 percent.
For Cody, the test is whether the capacity created by AI improves the team’s ability to pursue, win, and deliver profitable business.
Cody’s suggestion for growth teams is to use the measures leadership already trusts: time returned to customer-facing activities, proposal development cycles, qualified pipeline, win rates, and forecast accuracy. A tool that cannot be tied to at least one of those measures is still an experiment.
The Advantage Is in How The Time Is Used
As companies establish their 2027 priorities, AI investment should begin with the work itself rather than a list of available technologies.
For business development teams, much of the opportunity lies in activities that are necessary but do not independently create customer value: gathering information, preparing documents, updating records, and coordinating decisions.
Cody’s perspective is that reducing this burden creates an opportunity, not a guaranteed result. Organizations still have to decide how that recovered capacity will be used.
More time can mean deeper customer engagement, better-qualified pursuits, stronger proposals, and more disciplined execution. Or it can simply mean producing more activity.
AI can give growth teams back their time. The competitive advantage comes from what they do with it.
