Are all these AI tools actually worth what we’re spending on them? |
This question echoes in my mind each time I log in to an AI tool to accomplish a work-related task. And I continue to use these tools with an unflagging optimism that it will indeed be worth the fees.
Last week, our marketing expert Audrey Rawnie Rico explored the future of the AI economy for sales and marketing teams. Now, I want to dig into what comes after adoption.
Here’s what we’re seeing: According to a recent study by McKinsey & Company, over 80% of companies using AI report no tangible bottom-line impact. Meanwhile, the Wharton Human-AI Research found that AI usage in marketing and sales tripled, from 20% in 2023 to 62% in 2024. And yet, meaningful ROI is still elusive.
|
|
|
The usage of Gen AI in sales and marketing tripled from 20% in 2023 to 62% in 2024. (Source: Wharton Human-AI Research 2024) |
At my company, we jumped headfirst into AI tools across our content workflows, including drafting ideas, automating processes, and experimenting with new formats. And honestly? It’s been transformative in some ways, but underwhelming in others. More tools didn’t automatically mean better outcomes, especially when we weren’t clear about how we’d measure success or who owned which part of the AI budget.
So today, I’m leaning into one crucial question: How do we move from AI adoption to real alignment? Because the plugins are here, the experiment phase is over. What’s needed now is a strategy that ties human insight to tech investment so that we’re not just using AI but making it work for us. |
|
|
Aligning AI adoption with strategic purpose |
I asked several industry experts to shed light on these AI budget wars. SEO Meetup Founder Ross Kernez said having a shared budget for AI tools will keep things organized, but might create issues over shared access.
He added that once you figure out what works for your team, “you will get the most out of AI even if the ROI isn’t always obvious.” Otter Public Relations’ publicist, Manuel M. Grajeda III, echoed this, noting that they reserve part of their AI budget for structured experimentation.
We are squarely in the era of AI ubiquity, yet real integration still lags. According to the AI Marketing Benchmark Report, 69.1% of the 1,290 marketers surveyed reported using AI in their marketing operations. However, only 34.1% claim they’ve achieved significant outcomes.
Meanwhile, a deeper look at enterprise readiness shows that only 34% of organizations have formal AI policies in place, and just 36% have established ethics frameworks, leaving nearly 71% of teams without an AI roadmap.
The gap is clear: Tool stacks are growing, but strategy isn’t. We often celebrate adoption rather than evaluating results. Many marketing teams have embraced generative AI for content production and personalization, but the real winners will be those who link adoption to alignment.
So, it’s time to ask, how does each tool tie back to business goals? How is AI enhancing our messaging and our meaning, not just our output? To shift the balance, it’s time to recast AI as a strategic partner and simplify your stack: |
- Reduce redundant platforms and focus on tools that amplify your core narrative.
-
Create a governance framework for training your teams, defining ownership, and mapping AI’s role from ideation to outcome.
- Finally, measure what matters. Move beyond metrics like “outputs generated” and track metrics like “customer feedback loops initiated” or “topic authority established.”
|
The next chapter of marketing leadership will be defined by alignment plus intention, not just automation. Teams that center human insight alongside machine capability will turn the promise of AI into a strategic advantage and leave the era of tool overload behind. |
|
|
From tool spending to real returns |
Sales teams are no strangers to shiny new tools, especially when AI promises higher productivity, sharper insights, and faster deals. But as budgets balloon, so does the question hanging over every revenue leader’s head: Are these tools actually working?
A recent Boston Consulting Group survey found that 74% of companies struggle to achieve and scale value from their AI efforts. And only 26% of organizations have the capabilities needed to move beyond proof of concept and into meaningful impact.
As Investopedia points out, many AI companies (and by extension, their customers) are struggling to deliver meaningful ROI. This is often because of poor workflow integration and a lack of domain expertise.
Still, when implemented correctly, the payoff is real. MarketsandMarkets reports that AI-powered sales tools have achieved 91% forecasting accuracy compared to 67% for traditional methods, and can improve performance by up to 34% within 60 days of implementation.
The message is simple: You don’t need more AI; you need measurable AI. Before approving another budget request for AI tools, ask three questions: |
- Does this tool directly reduce admin work or accelerate decision-making?
-
Can it integrate with how my team already sells?
- Can we prove its value beyond dashboards in actual closed deals?
|
Sales success in the AI era isn’t about spending more, but spending smarter. When every tool is tied to outcomes rather than mere optics, that’s when AI starts delivering the ROI it promised. |
|
|
Submissions have been edited for length & clarity |
|
|
|
“As marketing and sales teams rush to embrace AI tools, it’s critical to move beyond experimentation for experimentation’s sake and instead adopt with clear intent and purpose. Every AI investment should tie back to a clear objective, whether that’s reducing manual effort, eliminating the need for more costly alternatives, or creating more revenue potential by improving lead quality, increasing conversion rates, or enhancing customer engagement. Before adopting or integrating new tools, teams should define the specific outcomes they’re seeking and align those outcomes with measurable KPIs.”
Tyler Lessard, CMO at TechnologyAdvice |
|
| Same tech, different truths |
Marketing is doubling down on AI to prove efficiency by automating campaigns, scaling personalization, and chasing performance metrics that show progress on paper. “The data looks great,” they say. “We’re finally proving ROI.”
Meanwhile, sales is having a different experience. Their dashboards are full, but their days are heavier. The CRM is bursting with AI-generated insights, yet closing deals feels more complex than ever. “We’re getting more information,” they say, “but not more clarity.” |
|
|
→ Translation: Marketing sees AI as proof of productivity. Sales sees it as proof of overload. |
|
|
The hard truth is that AI adoption doesn’t equal alignment. You can use the same tools and still speak entirely different languages. The fix? Context over convenience.
Marketing can translate what their AI insights mean for real customer behavior, and not just performance dashboards. Meanwhile, sales can share what those customer conversations reveal about the limits of automation. Together, they can decide where AI truly adds value and where the human touch still wins. |
|
|
|
Bianca has spent the past four years helping businesses strengthen relationships and boost performance through strategic sales and customer engagement initiatives. Drawing on her experience in field sales and territory management, she transforms real-world expertise into actionable insights that drive growth and foster lasting client partnerships. |
|
|
Selling Signals is a TechnologyAdvice business © 2025 TechnologyAdvice, LLC. All rights reserved. TechnologyAdvice, 3343 Perimeter Hill Dr., Suite 215, Nashville, TN 37211, USA. |
|
|
|
