Sales robot holding uo the words AI

Every CRO or CSO is investing or pondering the AI related tools acquisitions for their organization. Makes sense. What is the core objective? Increase the efficiency of how sellers process their tasks in very busy days? Increase sales team effectiveness? Create competitive advantage? Sell more? All are reasonable, but here is a reality check and a recommendation.

AI DOESN’T CREATE ADVANTAGE, SYSTEMS DO.

DON’T USE AI TO FIX SALES SYSTEMS. FIX SALES SYSTEMS—THEN USE AI TO SCALE THEM.

We talk a lot about Efficiency versus Effectiveness. To be clear, we are in the Effectiveness business. Let me provide some simple definitions to create clarity on terms that often get confused.

SALES EFFICIENCY is about how to get in front of the right customers, for the right amount of time, at a minimum cost. Good measurements include Cost of Sale, Participation Rate, Call Volumes and Call / Prospect Ratio. Focus is more or less of something and speed.

SALES EFFECTIVENESS is about how to maximize sales potential once you are there. Good measurements include Win Rate, Average Deal Size, Attach Rates, Sales Cycle Length, and Call / Deal Ratio. Focus is Better.

Sales Organizations like to invest in tools and the sales stack has become very thick and generally under-utilized. A few years ago, we identified 20 different categories of sales tools. This was pre-AI. We then categorized them as either Effectiveness tools or Efficiency. 90% were Efficiency focused. When organizations look to invest in AI, as you may have guessed, the “use cases” are generally focused on speed, more, and thus efficiency. For someone who uses AI daily, the speed component is super helpful to get started on simple research-related tasks and other tasks. Human intervention is then required to inspect, modify, and customize the AI outputs or potential “slop”.

At a bare minimum, all staff should have access to an AI tool [free or otherwise]. They should be using it for research on industries, companies, roles and people to help build credibility and understanding. This helps with messaging and positioning. This is about efficiency but can also improve effectiveness. My Partners are experts in curiosity, which is another key differentiator in high-performing sellers. Curious people dig deeper and look for connections in information to create stronger insight, perspective and credibility.

Enterprise sales are hard work. It has gotten much more challenging in the last 10-plus years for well-documented reasons, such as:

● Well-educated buyers who have made a bunch of decisions before they engage vendors.
● Very large buying groups with disparate interests.
● Resource constraints and risk aversion lead to the status quo bias.
● Increased competition and economic sensitivity.
● Complexity of decisions and volume of info that is potentially contradictory.
●  Add your next three favorites….

As a sales leader, the weight of trying to achieve aggressive growth targets on the back of the points above, with your limited resources, forces hard choices. That is the nature of strategy, and in this case, Sales Strategy. So, where should AI fit into this Strategy?

We are providing a sequence of potential investments in AI for a sales organization. Investing in AI and trying to put it into or on top of a poorly functioning GTM system is not helpful. You may drive some minor efficiency improvements, but not real business outcomes you care about. A good starting point, based on known challenge areas, is to:

1. INVEST IN WORKFLOW REDESIGN BEFORE AUTOMATION.

We use the term Sales Motion to define the detailed [and hopefully differentiated] way that a sales organization consistently tries to execute their go-to-customer strategy. This is the most integral component of any sales system. Without adding more definitions, the broader sales system builds in the workflows, rules, roles, technology systems, data, processes, reporting and governance that dictate how a sales organization really operates. This is the typically the domain of sales operations and enablement. Before you consider more automation through AI, it is prudent to inspect and understand how things work today [or not]. This will help identify key breakage points, constraints and challenges that require process and workflow redesign.

Once you have identified what needs to change, you can think about how AI automation can support that change based on the desired efficiency improvement.

2. CLEAN AND SIMPLIFY DATA (FOUNDATION LAYER)

Most clients complain about poor quality CRM and funnel data. Garbage in, garbage out obviously impacts data quality and thus layering BI and AI on top of poor data does not add value. AI depends on signal quality not data volume. Quality data creates the right signals which leads to better quality tactics and decisions. This gives AI something to work with.

3. BUILD SALES INTELLIGENCE & SIGNAL LAYER

The fundamentals of segmentation, targeting and positioning come out of understanding your ICP. The Personas imbedded within the targeting lead to clear and insightful positioning of the business problem and corresponding impact that hopefully resonates with those job titles. We use the term “verifiers” as part of a Sales Motion to define measurable actions the client has taken that indicate they are moving forward to the next step. Signals are similar and are the subset of data that predict customer behavior.

AI doesn’t “create magic.” It does three things with signals:

I. Identifies Signals (Finding patterns humans miss).

II. Scores Signals (Separating signal from noise)

III. Activates Signals (Telling you what to do)

In the spirit of the efficiency versus effectiveness differences, we are seeking “better” signals not “more” signals.

4. IMPROVE IN-CYCLE EFFECTIVENESS (WHERE DEALS ARE WON)

With a well-defined Sales Motion, you have clear understanding at a team and rep level [in measurable ways] what your high performers are doing versus the rest of the team. You gain clarity at each stage of where your organization is effective and where you are not. AI can help sharpen messaging to open doors and to do much better discovery. It can help analyze call recordings and provide high level coaching guidance based on what you are looking for from seller behaviors. It can identify deal risk, competitive strategy and potential powerful requests of what you want the prospect to do next that adds value for them and deal momentum. You need the underlying systems, measures and data quality, but AI can support a well-considered and governed Sales Motion.

5. BUILD FEEDBACK LOOPS (LEARNING SYSTEM)

We need to know whether our messages are resonating, if our tactics are moving us forward and why we win or lose. This is about continuous improvement. AI can help create a learning system based on its ability to analyze quality data and make structured recommendations. This could impact targeting, messaging, deal strategy and pricing models. You can train AI to be a learning engine, not just a tool.

6. APPLY AI TO FORECASTING & DEAL INSPECTION

This area is potentially dangerous based on data quality. Most CFO’s I know discount CRM data for forecasting purposes and apply the human element or gut instinct. They get inside big deals and apply experience to modify and de-risk CRM forecast data. That said, AI can apply deal scoring and evaluate pipeline risk based on the identified signals.

7. SCALE WITH AUTOMATION (LAST, NOT FIRST)

This is the biggest mistake companies are making right now as they seek to apply AI. They are making these moves first. A recent piece of Gartner research [April 14, 2026] indicated that AI is not improving sales productivity. Companies are adding outbound sales automation, which will meaningfully increase volume, but it is likely getting lost in the volume of generic slop sitting in your target personas inbox. AI is creating content rapidly and building proposals in minutes, not days. Not bad things but may not help overall effectiveness of your teams. We talked about workflow automation earlier, but it needs to be a quality workflow. The objective is to scale components that work. We can find efficiency, but we cannot degrade effectiveness at the same time.

AI Investments In Sales - Final Thoughts

In 2026, every sales organization will have access to the same AI tools. Faster outreach, automated workflows, and instant content creation will become table stakes. The difference will not come from what you buy, but from how well your system is designed to use it. If your underlying workflows are flawed, your data unreliable, and your signals weak, AI will simply amplify those weaknesses at scale. If your system is sound, AI becomes a powerful multiplier—sharpening decisions, improving execution, and accelerating outcomes that already work.

So, the question for sales leaders is not, “Where should we apply AI?” It is, “Do we have a system worth scaling?” The organizations that win will resist the urge to move faster for the sake of speed. They will fix what matters, focus on the few things that drive outcomes, and apply AI with precision. Do less. Do it better. Then—and only then—let AI scale it.