Over the past couple years, the sales technology landscape has exploded with AI promises of instant pipeline, seamless automation and game-changing leverage. Yet, we often see other sales leaders getting caught in a constant cycle of adding new platforms, only to see pipeline velocity stall and reps grow increasingly frustrated.
Sure, we all love a new tool, but, as you take your AI sales tech passed pilots, you have to be more sensible and strategic.
When our CEO Rick Pizzoli recently brought strategic consultant Ken Grosso and me together for a LinkedIn Live panel on AI and sales strategy, a clear pattern emerged. Sales leaders are tending to buy new tools out of anxiety and fear of falling behind. And then they layer these new shiny AI tools directly onto broken processes, which then the tech magnifies existing chaos.
Buying a hyped up AI tool is easy. Ensuring it actually delivers bottom-line productivity is where the real work lives. Having led revenue teams through lead generation, enterprise sales and channel expansion, my team and I have seen firsthand what works and what fails when bringing tech — and especially non-deterministic AI — into a sales workflow. If you want to avoid tech stack bloat and build a high-performing revenue engine, here is how you should evaluate sales tech before adding it to your organization.
Listen to the full conversation: AI in Sales Right Now
The single biggest mistake sales leaders make is treating software and especially AI as a cure for an operational problem. If your sales team suffers from inconsistent messaging, poor qualification or undefined deal stages, adding an AI tool will only help them execute bad habits faster.
During our session, Ken put his finger right on the issue, explaining that "leaders and companies are feeling so much pressure to implement AI tools because they're afraid they're going to fall behind or lose their job.” They buy these tools only to layer them on top of broken sales processes. “And what it does is, instead of helping them, it actually magnifies the cracks and amplifies the chaos a bit."
Top industry analysts echo this exact dynamic. According to Gartner's ongoing revenue research, less than 10% of sales leaders feel their tech stack delivers high value when underlying sales processes lack discipline. Furthermore, our partners at the Sales Enablement Collective found that just only 5% of revenue leaders can point to significant, quantified impact on revenue metrics.
Before you evaluate vendor features or request a demo, step back and conduct a thorough audit of your underlying sales engine:
If there are cracks in your sales process, fix the plumbing first. As Google’s annual DORA report has found, AI is consistently proven to be an amplifier: layer it over a broken system and you amplify the chaos; layer it over a sound process and you create true leverage.
When we ask executive teams how a specific tool is making their sellers more productive, we often get blank stares. Organizations buy tools with a vague goal—like predicting revenue more accurately or increasing outreach — without setting concrete parameters for success.
As Rick pointed out during our discussion, there is a distinct disconnect happening across the industry. "I read that there's been a 90% increase in AI investment in sales, but a 5% reduction in productivity," Rick observed, adding that "if salespeople are being more efficient, how are they using that time to spend more time with the clients?"
Kevin Phelan, our UK sales operations manager, highlights why leaders need to push back against the constant stream of new vendor promises:
“There are new SaaS tools hitting the market every day with AI enabling smaller developers to release viable products much more easily. Many of them target niche solutions, unique pricing models, etcetera. And they sound like 'the key to transformation.' In this environment it's necessary to be extremely skeptical, and clear-eyed about what you need and what a solution is worth. Ask: Will this tool really impact the business? and, if so, Does the return outweigh the cost?"
Before signing a software contract, specify the exact operational metric the platform must improve. Ask your team:
Historically, solving a software gap required buying an expensive and/or long-term enterprise subscription. Today, generative AI and low-code platforms allow revenue teams to build tailored internal tools without massive engineering overhead.
"AI also offers great opportunities to develop internal tools that would have previously required skilled coders. Often, the core benefits of premium products can be achieved at a much cheaper price with a little internal work,” Kevin explains.
“This can allow greater customization too. While larger businesses may have deeper pockets, smaller teams can usually leverage their flexibility and narrow focus. For example, we regularly hear of small sales teams vibe coding their own mini-CRM apps rather than pay for costly subscriptions to the major enterprise CRMs. This was rarely feasible in the past, but now it's becoming common practice."
When evaluating a new SaaS platform, ask whether a lightweight internal app or custom orchestration prompt could achieve 80% of the functionality at a fraction of the cost.
A new shiny tool is useless if its data sits isolated from your core revenue systems. Data silos create friction for reps and blind spots for operations.
McKinsey's research on enterprise tech architecture emphasizes that the highest returns on sales technology come from connected ecosystems where data flows seamlessly between systems, rather than isolated point solutions.
Kevin stresses connectivity as a non-negotiable evaluation criterion: "Ensuring a new tool has a reasonable level of connectivity with other tools – MCP, native integration with orchestration tools like Make/Zapier/n8n, a substantial API – will avoid a lot of problems down the line. One of the most annoying problems Ops can face is accessing data that a tool has made inaccessible. I would much rather have a tool that lacks some bells and whistles but its core service is strong and it has good connectivity."
For companies expanding into international markets — such as US firms launching into and across Europe — evaluating tech requires a regional lens. A tech stack or outreach playbook that works in a domestic market will rarely translate seamlessly overseas without adaptation.
European data protection laws (such as GDPR) place strict limits on automated data scraping, outreach sequencing and call recording. Furthermore, just because an AI outreach campaign works in the UK doesn't mean it will work in Germany or France. A sales tool must allow local execution teams to adapt messaging, tone and positioning for regional buyer behavior.
Finally, budget for enablement, not just licenses. One of the main reasons sales tools fail is that companies invest 90% of their effort into buying software and only 10% into enabling reps.
Ken highlighted this internal consistency gap during our discussion, noting that "there should be a set of parameters and expectations on why the tool was purchased and how it can make the team more productive. But I feel like it's 80/20 in the opposite direction right now. And that's what's causing a lot of the chaos."
At Sales Force Europe, we advocate for an 80/20 approach to enablement:
It is easy to get distracted by the next AI sales tool that promises an effortless pipeline. But sustainable sales growth has never been about accumulating software licenses; it’s about building a disciplined, repeatable revenue engine.
Structured processes and solid planning must come before tech execution. You don't need to implement everything all at once to stay competitive. Find the specific places where technology can make a genuine difference first, evaluate those tools against clear metrics, ensure good system connectivity and train your team properly. Fix the underlying plumbing first, and your sales technology will finally deliver the leverage and scale it promised.
