One of the biggest questions I think anyone needs to ask when considering using a new technology is: Does this help me do things better, or do better things? As in, can I do what I currently do but a bit faster, a bit cheaper, a bit easier? Or can I do something I couldn’t do before? 

In sales, I think AI is the latter, being treated like the former, and it risks making the problem we're trying to solve with it worse. Let me explain.  

There are only so many hours in the day, and account management comes with an awful lot of work before you get anywhere near selling. There are customer issues to resolve, meetings to prepare for, orders to chase, emails to answer and internal requests to deal with.  

Then there’s the work involved in finding the information you need across CRM, ERP, email, dashboards, reports and wherever else it happens to live. Not to mention all the work of putting information into the CRM.  

If you’re responsible for a large book of business (and let’s face it, most reps are), keeping on top of all of that is difficult enough. Working proactively across every customer is another matter entirely. 

So people make perfectly sensible decisions about how to spend their time. They focus on the accounts they know need them. They deal with the customers making the most noise. They keep their own notes because it’s quicker. They maintain a spreadsheet because it works for them. They update the CRM when they get a chance. 

From their perspective, they’re getting the job done.  

Unfortunately, those perfectly rational decisions create problems elsewhere. 

The sales leader wants their team spending more time with customers, but also finds themselves chasing CRM updates because they need to know what’s going on. 

The CRO wants better coverage of the customer base and more revenue, while also needing accurate information to understand whether the business is going to hit its numbers. 

Leadership needs reliable customer and pipeline data to forecast and make decisions, but some of the most useful information is sitting in inboxes, spreadsheets, notebooks or people’s heads. 

And IT, having invested in systems intended to create a reliable source of customer information, ends up supporting a collection of workarounds alongside them. 

This is how you end up with a situation where everyone is asking for something reasonable, but collectively we’re asking sellers to do two opposing things: spend more time selling, and spend more time maintaining the information the rest of the business needs. 

Surely this is exactly the sort of thing AI should fix?  

There’s no shortage of ideas for applying AI to sales. You can use it to write emails, summarize calls, research accounts, produce reports, draft follow-ups and answer questions about customers. 

All useful things. But all fall into the camp of ‘do things better’. 

Given how overloaded sellers already are, I think there’s a more interesting question to ask: Can AI reduce the amount of information and administration they have to deal with in the first place? 

Take a seller with 80 accounts. 

Giving them an AI assistant that can summarize any account in seconds is obviously better than asking them to spend 20 minutes researching it themselves. 

But they still need to know which account to ask about. 

That distinction matters. 

There’s a big difference between technology that makes it easier for someone to extract information and technology that brings the right information to them when they need it. 

If one of those 80 customers has suddenly reduced its order volume, why should the seller have to go looking for that information? 

If an account that normally orders every six weeks has reached week eight without placing an order, why should someone have to remember to check? 

If something has changed that means an account deserves attention today, why wait for the seller to find it? 

This, to me, is where AI starts to get genuinely useful. Not as another place for sellers to go looking for answers, but as a way of doing more of the looking for them. This is where we start to transition into ‘doing better things’.  

Because if a seller is presented with next best steps based on information they need but didn’t know they needed, suddenly they’re able to serve way more of their customers with a personalized level of service that wouldn’t have been possible before. 

More AI could quite easily mean more overwhelm 

There is a danger here, because AI is extremely good at producing things. 

Give it some customer information and it can produce a summary. Give it a call recording and it can produce notes. Give it a data set and it can produce insights. And because producing all of those things is now cheap and easy, we can produce an awful lot of them. 

Which is great, right up until someone has to read them. 

If we’re not careful, we’ll spend the next few years layering AI-generated summaries, recommendations, alerts and insights on top of an already overwhelming amount of customer information, then congratulate ourselves for making sellers more productive. 

The better test is probably much simpler: Does this mean the seller has less work to do? 

Does it reduce the amount of time they spend searching for information? Does it mean they can work effectively across more of their customer base? Does it remove some of the administration that stops them spending time with customers? Does it help the business get better information without relying on the seller to constantly feed the machine? 

Because if AI can do those things, we start to resolve the contradiction. 

Sellers get more capacity to sell, without leadership sacrificing the visibility it needs to run the business. Useful customer information can come from the systems where it already exists rather than relying on someone to re-enter it. IT can spend less time supporting the workarounds that spring up when people don’t find their core systems useful. 

That’s a much more interesting promise than generating a meeting summary a little faster. 

Which brings us back to CRM 

There’s an awkward question underneath all of this. 

CRM has spent decades promising to help sellers sell and businesses understand their customers. Yet sellers are overwhelmed, adoption remains a problem, customer information still escapes into spreadsheets and notebooks, and leadership still struggles to get a reliable picture of what’s actually happening. 

So how did we get here? 

Our CEO, David Roberts, has spent more than two decades working in CRM, first advising organizations on CRM strategy and implementation at Accenture and now from the other side of the table at SugarAI. 

In his new paper, Precision CRM: Making good on the failed promise, he looks at why CRM has failed to deliver on parts of its original promise, how the problem it needs to solve has changed, and why AI gives us an opportunity to finally do something about it. 

If you’re thinking about how AI can help your sellers spend more time selling without sacrificing the customer intelligence the rest of your business depends on, it’s worth a read. 

Read Precision CRM: Making good on the failed promise