AI has been hyped as the silver bullet for customer service and sales, and nowhere more than in chatbots. The promise was simple: let machines handle customer contact so humans don’t have to.
But the reality has been far less elegant. People can smell a bot from a mile away, and nothing kills trust faster than a canned AI response, especially in sales, where the goal is to ask customers to part with their hard-earned money.
The irony is that while companies pour resources into teaching AI to build relationships (the one thing it’s still objectively terrible at), they ignore the real bottleneck strangling performance: information overload.
Customer service and sales are execution-heavy jobs. Great teams succeed by talking to people, adding value, and moving fast: not by deciphering endless dashboards and Excel dumps.
Yet most organizations bury their teams in data while outsourcing the work they’re actually good at to “virtual agents.” By the time reports or KPIs arrive, they’re already outdated or too granular to act on.
Faced with this flood of unusable information, both reps and managers tune it out and get back to what they know best: winging it. The result? Paralysis.
...nothing kills trust faster than a canned AI response...
Human-centric processes rarely fail due to a lack of data. They fail because the wrong data, delivered the wrong way, turns potentially valuable insights into noise.
We’ve now reached a crossroads where too much of the wrong information is intersecting with inefficiently used AI. We must stop confusing automation with intelligence; AI should be used to amplify human performance, not replace it.
A Fork in the Road
Anyone who’s ever interacted with an AI bot knows you can get around it by demanding to speak to a human.
This means most people who encounter real people in contact centers come with one of two scenarios. A: they were already upset by being met by a chatbot and are in a bad mood. Or B: the chatbot didn’t give them the correct answer, either because of bad prompts or insufficient background data.
In both cases, the customer representative is starting the conversation with someone who’s already in a bad mood: and with limited information about why they got in touch in the first place.
A simple answer to this problem is to avoid AI tools altogether. But that would mean walking away from one of the biggest productivity revolutions in human history.
The choice isn’t whether to use AI, but where to use it. Do we automate human interactions? Or do we automate the friction around them – the overload, the lag, the guesswork – so as to focus on what humans do best? That choice will determine which companies pull ahead in the next decade.
Shouldn’t AI Take Care of the “Grind”?
Indeed, the ideal AI doesn’t replace salespeople. It removes friction so they can perform at their best. Used properly, AI can:
- Surface real-time insights as they happen so reps can act instead of analyze.
- Transform endless dashboards into a single clear recommendation with the next right steps to take.
- Handle the data crunching and pattern recognition that machines excel at, while leaving the trust, context, and negotiation to people.
- Scale human outreach without turning it into spam, helping prioritize who to contact and when, thereby making communication timelier and more relevant.
Some will argue that automating outreach is the smartest way to use AI in sales. Why rely on one rep to write 50 emails a day when an AI can send 5,000?
In that view, sales is a numbers game; more messages mean more meetings and more meetings mean more deals. Prospects might roll their eyes at yet another bot-written pitch, but if even a small fraction converts, the math still works.
However, this logic misses the bigger picture. What looks efficient in the short term erodes credibility in the long term.
Just as inboxes became immune to cookie-cutter cold emails, they’ll quickly tune out AI spam. Unlike cold calling, trust is far harder to rebuild once prospects learn to filter out the noise.
While AI-generated outreach might yield a bump in meetings, the cost is cumulative. Every impersonal message teaches your audience that your brand isn’t worth listening to.
AI as Extension of the Mind
To overcome this, we must treat the new tools as an extension of our minds. A storage cache where we can easily retrieve the data we need and get the big picture whenever we need it.
Whether it’s a specific customer or a broader strategy for upsell and customer satisfaction, having access to all the company’s data in a “second brain” is critical to make a better organization. A perfect AI for sales and customer support does not talk for the reps. Instead, it strategizes with them.
...[sales] needs AI to think with them.
After all, the human brain is better than any other system at retrieving information quickly. Millions and millions of impressions can be brought to mind whenever a person wants to relive a moment or make a decision.
What the brain lacks is storage capacity. With thousands of data points from various sources, we have to make lists to keep track of them all. And when there are tens of lists with thousands of data points, we simply can’t do it.
For reps, this would mean access to insights about specific customers or prospects that they would otherwise not have time to look for. For managers, the ability to access the right data whenever they need it will give them both more time and better insights.
In other words, sales does not need AI to talk for people. It needs AI to think with them.
Instead of dumping spreadsheets or dashboards on a team, AI can synthesize the noise and surface the few insights that actually matter. Namely who’s warming up, who’s about to churn, and which activity today will move the needle.
That’s the leverage point: a layer that makes data usable in real time. When it works this way, automation amplifies the human in the loop, rather than reducing their role.
In the end, the sales teams that win with AI won’t be the ones that replace their people. They’ll be the ones who finally free them to do their best work. The future of sales isn’t automation; it’s amplification.