Most B2B sales teams don’t have a talent problem. They have a capacity problem.
Administrative drag is quietly stripping selling time: CRM updates, stakeholder mapping, duplicate cleanup, meeting summaries, and the constant “what should I say next?” work that should not be consuming a senior seller’s day. The downstream damage is bigger than annoyance. Forecast accuracy declines, coaching becomes reactive, and revenue management turns into a negotiation with incomplete data.
Artificial intelligence can fix this, but only if you use it with the right operating model.
Benjamin Todd’s article “How not to lose your job to AI” makes the point that AI doesn’t simply eliminate jobs; it shifts where value concentrates. As routine tasks become cheap, the remaining human bottlenecks become more valuable. Todd’s ATM example is the cleanest version of the idea: ATMs reduced the need for “money counting,” but the overall demand for human banking roles didn’t collapse. The job shifted toward customer-facing work and higher-leverage conversations.
In B2B sales, our “money counting” is CRM entry, list building, and manual research. Our high-leverage work is business acumen, strategic influence, stakeholder alignment, and value selling. The problem is that most teams have it backwards: humans do the hardest input work (research, logging, hygiene), then AI writes the customer-facing messages. That combination produces drained sellers and generic messaging.
A better model is: Automate the input, humanize the output.
Use AI and automation to capture facts, structure the data, and keep the sales processes clean. Keep the last mile human: judgment, tone, timing, positioning, and the nuanced messaging that builds trust. Todd calls this “communications and taste” in practice. AI can generate options, but humans decide what will land.
This is the shift from the Artisan Trap (handcraft everything) to a Cognitive Revenue Engine (direct a tech-led, human-centric workflow). Orchestration engines like n8n and Make.com become the connective tissue: they route meeting transcripts, CRM objects, email drafts, LinkedIn touchpoints, and task creation through a cohesive system. Rules-based automation preserves factual correctness; AI handles reasoning, summarization, and drafting when helpful; humans remain accountable for relevance and risk.
What changes in the field:
Cognitive prospecting replaces manual browsing. Instead of hunting for scraps, you set “listening posts” that surface triggers, new leaders, funding, stated priorities, cost language, so sellers start the day with real “why now” signals.
Immediate recap workflows remove post-call lag. Transcripts become structured notes, CRM updates, and a recap draft within minutes, not hours. That improves follow-up speed and protects deal momentum.
Always-on hygiene stops bad data from poisoning everything downstream. Deduplication and normalization prevent wasted enrichment spend and false pipeline math.
Predictive intelligence becomes usable because the inputs are trustworthy. When the data is clean, risk signals can be detected early enough to change outcomes.
Here are a few immediate action items a sales leader can do today
Run a Post-Call Lag Check. Pick three calls and time the gap from hang-up to follow-up sent and CRM fully updated. That number is your measurable “sales tax.”
Standardize the recap structure. Require every meaningful call to produce the same fields: pain, impact, stakeholders, budget, next step, and risks. Consistency is what makes AI and automation reliable.
Build one listening post for 10 accounts. Track executive changes, funding, initiatives, and cost containment language. Route alerts into a daily digest so sellers start in editorial mode rather than hunting mode.
Turn the recap into a workflow. Transcript → structured extraction → CRM update → tasks → recap draft for human approval. This is the fastest way to reclaim selling time without sacrificing quality.
If you take Todd’s argument seriously, the goal isn’t to “use AI more.” It’s to move human effort up the value chain. Reduce routine work. Increase the number of moments when humans create safety, clarity, and decision momentum for buyers.
The future of B2B sales isn’t about choosing between humans and AI. It’s about humans amplified by AI. Let’s build that future together.
If you’d like to explore this topic in more depth, there’s a podcast episode that covers all of this information and more. You can find the link below and consider subscribing to the podcast AI Tool for Sales Pros on your favorite podcast player.
