The new business development playbook: Winning with AI in today’s staffing market
At Engage Boston 2026, Keith Weightman, regional vice president of national accounts at Bullhorn, opened his session with a question: how many people in the room had lost a deal in the last 90 days because a competitor got there first, or because they didn’t even know the opportunity existed? Almost every hand went up.
That’s the problem this session was built to address. Weightman was joined by four practitioners already running AI-assisted business development in their firms. Nick DeFelice, co-founder and VP of operations at Take2, Jonah Rader, president and co-founder of Connected Healthcare, David Forde, senior consulting manager at Procom, and Jim Brashear, senior vice president at Planet Group. Each brought a different adoption story and a distinct set of tools. Together, they made the case that the gap between firms using AI for sales and those still waiting is widening fast.
Here’s what they covered.
Start with adoption, not tools
The panelists took different paths to AI adoption on the business development side, but they landed in the same place. The right technology only delivers results when the rollout fits the organization’s culture.
At Take2, the early push to get sellers using AI for outreach hit resistance fast. Salespeople are relationship-driven by nature, and the idea of automated client communication made them uncomfortable. The team adjusted. Instead of leading with external-facing outreach, they started with internal-facing use cases like research and call prep, work that let sellers build confidence with the tool without anything being visible to prospects. From there, curiosity took over.
Connected Healthcare leaned into a different instinct. As a younger firm with a team already comfortable with tools like ChatGPT and Claude, Amplify felt like a natural extension. The emphasis was on identifying what was taking people too long and using AI to get that time back. But speed wasn’t just an internal efficiency play. Faster responses also meant prospects weren’t left waiting, and deals that might have gone cold stayed warm.
“We want to get in early so we can fail fast, fail forward, and learn how it really can support all aspects of our team.”
— Jonah Rader, president and co-founder, Connected Healthcare
Planet Group built an AI Center of Excellence, not as a top-down mandate but as an open invitation to anyone who was curious. The focus was removing friction across the organization, especially for sellers who were so embedded in delivery work that they had little capacity to build pipeline. AI didn’t change the goal. It created the space to pursue it.
The common thread across all four firms was that adoption works when the rollout starts where sellers are most comfortable, not where leadership is most eager to measure results.
The tactical moves driving real results
Brashear walked through how he used Amplify to pull 300 stale contacts at one company, and then asked it to build a seven-step call plan with dates, prioritized by title, relevance, and past conversation history. Each phase came with a completion percentage he could track in one-on-ones. The tool didn’t just find the contacts. It told his sellers who to call first, and why.
DeFelice’s team built a workflow that combines Amplify’s web access with historical Bullhorn data. A seller starts with a target list of 15 accounts, asks Amplify to identify open jobs across those companies in real time, then asks it to match those openings against past placements in similar roles. The result is a call that opens with proof of performance rather than a pitch.
Rader described using Amplify’s Global Chat mid-call, not to replace preparation, but to handle the curveball questions that used to end with “let me get back to you.” When a client asks something specific about placements, markets, or metrics, the answer is now available in the moment. The volume of deferred responses has dropped significantly at Connected Healthcare, and the quality of conversations has changed as a result.
Forde highlighted a different application. By asking Amplify to surface conversations where strong interest was expressed and no follow-up task was set, sales managers now have visibility into deals that might otherwise slip. A Friday recap prompt pulls that same view together, giving leaders a clear picture of where their team’s attention should go the following week.
Why Amplify sits at the center of the stack
All four firms run tools alongside Amplify, including LinkedIn, ZoomInfo, and enterprise AI platforms like Claude and Copilot. What stood out was how consistently Amplify became the connective layer rather than just another application. General-purpose AI tools work with what you feed them. Amplify works with what is already in Bullhorn, like placement history, contact records, open jobs, and client activity. That access to live data is what separates it from everything else in the stack.
Take2 made this explicit, steering sellers away from copying Bullhorn data into external platforms and keeping the workflow inside the ecosystem. Connected Healthcare took the same approach with specialized tools, using a purpose-built RFP platform that helped their two-person team go from two proposals per month to 15 to 20, while keeping the underlying candidate and client data centralized in Bullhorn.
The value of any AI tool scales with the quality of the data behind it. Amplify’s advantage is that it sits inside the platform where that data already lives.
Measuring what changes
One audience question cut to the heart of the session. Are you changing KPIs for your sales team now that AI is part of the workflow?
The honest answer from all four leaders was not fully yet, but the conversation is happening. What’s already shifting is the expectation around relationship volume. How many clients a seller can manage, how many unique billing relationships should be active, and how many departments within an existing client should be penetrated. AI doesn’t just speed up existing work; it’s expanding what sellers can take on.
Some firms are starting with activity-based metrics as a foundation like call volume, follow-up rates, and pipeline movement, before locking in output benchmarks. Setting benchmarks early, before adoption is complete, gives firms a cleaner baseline to measure against when they’re ready to make the call on revised targets.
At Connected Healthcare, quota expectations have already moved. The logic is straightforward. If the tool is working, the team should be doing more with the time it creates. If the numbers aren’t going up, it’s a signal to look at whether the tool is actually being used, or used well.
New hire ramp time is another area where firms are already seeing movement. When the onboarding process doesn’t require training on multiple external job boards, new sellers learn one system, get on the phone faster, and earn commission sooner.
When the whole organization starts innovating
The firms seeing the most progress have a clear answer to what they do with the time AI gives back. It goes into more calls, more relationships, more consultative conversations. Without that, the ROI never materializes.
When adoption reaches critical mass, innovation stops coming from the top. Sellers build their own prompts, share workflows in stand-ups, and find use cases no one anticipated. That’s the signal that something has genuinely changed. The firms pulling ahead aren’t waiting for perfect data or a finished roadmap. They’re starting, learning, and iterating. The gap between them and everyone else is growing every quarter.
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