In the Making Sense of AI for Sales Operations training session, we cut through the hype around artificial intelligence and demystify many of the core concepts. We talk about how AI has evolved over time and how it’s actually been in commercial use for many decades. We discuss the differences between Traditional AI and Generative AI and explore the various ways these technologies are now being accessed and leveraged by companies, large and small.
But one of the most important takeaways from this session is also one of the least flashy…
AI is dramatically lowering the barriers to building systems and tools.
Historically, to get the systems and applications we needed to do our work and optimize the sales machine, Sales Ops has either had to 1) purchase something big and expensive from an external technology vendor, or 2) wait for our internal IT teams to build, integrate, test, and refine something for us.
Of course, neither of these options is particularly cheap, easy, or timely…and there’s always an arduous gauntlet of approvals and justifications to navigate for budget and resources.
So it’s not too surprising that over time, many in Sales Ops have learned to stifle our aspirations, temper our expectations, and shrink our requests and proposals.
We’ve learned to stop asking for systems that just feel “too big” or applications that just seem “too complicated.” We’ll postpone developing new capabilities that might trigger a six-month documentation process and a multi-session grilling by the budget review committee. And eventually, all of our biggest ideas and most transformative initiatives are just quietly moved to the back burner…or they’re pushed off the stove entirely.
Instead, we learn to settle for things that are….shall we say…a bit less ambitious? Cleaner dashboards. Faster reports. Better CRM data hygiene. Tighter sales process definitions. More standardized templates and defined playbooks.
Now don’t get me wrong…these are all useful things. But we have to be honest and admit that these aren’t the biggest levers we could be pulling to improve overall sales performance and financial contributions.
But thankfully, the past isn’t always prologue…
As we discuss in the Making Sense of AI training session, the combination of Traditional and Generative AI is rapidly changing the economics and logistics of systems development.
Leveraging these powerful technologies, AI systems engineers are now able to “vibe code” working application prototypes over a weekend. In minutes, they’re now able to combine, clean, and transform massive volumes of data. And they can now connect disparate systems and build automated workflows in just a matter of days, instead of the months or even years that might have been required in the past.
Simply put, AI is rapidly and dramatically eroding the “cost” component in the cost-benefit equation for advanced Sales Ops systems and applications development.
And in turn, this means that many of the ideas, initiatives, and capabilities that we’ve had to postpone or even scrap for being too big, too complicated, too time-consuming, and too expensive in the past, may now be coming well within reach. Things like automatic whitespace analysis, defection detection, playbook matching, dynamic forecasting, and next-best prospect identification may no longer be stuck on the “maybe someday” list.
The point is that as AI changes the math and broadens of the definition of what’s both possible and cost-effective, it’s important that we break the habit of settling for less and give ourselves permission to think bigger again.













