For a long time now, being effective in Sales Operations required knowing how to do some pretty specialized things…
How do we pull all the CRM, opportunity, pipeline, customer, and financial data together? How do we clean it up and remove the noise? How do we structure accurate territories and reasonable quotas? How do we analyze pipeline health, forecast performance, rep productivity, conversion rates, and customer behavior?
And how do we identify and quantify an improvement opportunity, build a recommended action plan, and turn the whole mess into something the leadership team can actually understand?
All of this specialized know-how mattered a great deal because a lot of this stuff was genuinely difficult to figure out and execute.
But AI is quickly making the “how” a whole lot easier and more accessible.
AI can now help assemble and structure data. It can write queries, summarize research, identify patterns, generate hypotheses, run analytical routines, build presentations, draft recommendations, automate workflows, and explain complex concepts and analyses in relatively straightforward language.
And it’s only going to get better, faster, and more ubiquitous.
So…what happens when even the most specialized know-how becomes broadly available? Simply put, the differentiator shifts from knowing “how” to knowing “what, where, when, and why.”
After all, just because you can do anything, that doesn’t mean you should do everything. And commercial teams already have more potential problems to solve than they have time, money, or organizational patience to address.
Should we redesign territories? Revisit quota methodology? Clean up CRM data? Change pipeline stages? Tighten targeting criteria and opportunity requirements? Improve and automate predictive forecasting? Redesign management dashboards? Change lead-routing rules? Rework incentive comp plans? Improve customer-defection detection? Build better rep guidance at the point-of-sale? Or fix a broken handoff between Marketing and Sales?
Increasingly, AI can help us figure out how to do any and all of these things.
But it can’t tell us which ones matter most in our specific situation at this particular point in time, and which ones we should pursue first, second, and never.
Those decisions require much more than know-how…they require a high degree of acumen and discernment.
They require understanding the broader commercial situation well enough to define short- and long-term priorities. They require the ability to distinguish between root causes and symptoms. They require knowing when a pipeline problem is actually a pipeline problem…and when it’s really a targeting problem, an pricing or offering problem, an enablement problem, a management problem, all of the above, or something else entirely.
And they require an understanding of all the various factors and tradeoffs involved.
This is why the best sales operations in an AI-enabled world will not be the ones that use AI to automate the most processes, generate the most analyses, build the most dashboards, or produce the most recommendations.
The best sales operations will be the ones that consistently choose the right things to do with AI in the first place.
And the same applies to individual Sales Ops practitioners.
If AI makes it easier for everyone to pull data, conduct analyses, build workflows, develop recommendations, and create polished outputs, simply knowing how to perform those tasks becomes far less differentiating over time. So your differential value as an individual practitioner will increasingly need to come from knowing what really matters and why, and where and when to focus first, next, and never.
In an AI-enabled world, the specialized know-how to produce an answer is far less valuable than the acumen and ability to discern whether it’s the right answer to a question that’s worth asking.
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Making Sense of AI for Sales Operations
There's no doubt that artificial intelligence will transform nearly every aspect of sales and revenue operations. How do we cut through the hype and harness AI to generate improved sales results and business outcomes?
Aligning Sales Ops to Business Strategy
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