By Editorial TeamFor all the hype around AI, there’s a serious confidence problem in the C-suite. A new IAB report for 2026 finds that 68% of executives have significant doubts they’ll see a positive ROI on their AI spend within two years. That skepticism creates a huge headache for marketing and PR pros who are trying to spin stories of innovation, because it’s tough to project confidence to the public and investors when your own leadership is getting nervous.
Key Takeaways
- With two-thirds of executives doubting AI ROI in the next two years, PR strategies need to become radically transparent.
- Marketing needs to stop talking about AI’s “potential” and start showing specific, measured results like efficiency gains and other hard business outcomes.
- PR campaigns will work better if they highlight small, concrete wins (like a 15% drop in customer service response times) instead of pitching grand, futuristic visions.
- To handle the coming scrutiny on AI spending, companies should proactively share data-backed progress, even if it’s early, to get ahead of revenue doubts.
- Good communication means knowing what your specific stakeholders (investors, customers, employees) actually care about and tailoring the message directly to them.
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The 68% ROI Skepticism: A Call for Granular Proof
That IAB 2026 report gets right to the heart of the problem: companies are throwing money at AI, but the leadership can’t see the returns. That 68% figure is a blinking red light for PR and marketing teams, signaling that patience is wearing thin. Sweeping statements about “far-reaching AI” sound like empty noise when the board is demanding to see profitability data. We have to pivot from selling abstract potential to proving concrete achievements. For example, don’t just announce a new AI customer service platform. Instead, lead with the fact that it produced a demonstrable 15% improvement in first-contact resolution rates. That’s the kind of specific proof executives are actually looking for.
The Data Disconnect: Why Perception Lags Reality
A late 2025 analysis from eMarketer really puts a finger on the data disconnect: 92% of large companies say they have active AI projects, but only 35% can actually quantify the financial impact. That massive gap between adoption and proof is exactly where revenue doubts are born. The issue isn’t that the AI isn’t working. It’s that its contributions are being badly tracked and communicated. This means public relations strategies can’t be siloed. PR teams have to get in the trenches with product and finance to find the right KPIs that tie AI tools to real business value. Maybe that’s showing how predictive analytics cut inventory waste by 7%, or proving an AI content tool boosted marketing campaign speed by 20% with the same team size. In this context, the PR function has to be an internal auditor of value first and an external amplifier second.
Shifting Narratives: From Hype to Humble Wins
The old playbook for new tech was to build a grand, aspirational story to get attention. With AI, that has meant endless talk about AGI or dystopian sci-fi scenarios that, while fun, don’t do a thing to calm down an antsy CFO. That approach is broken. The market, especially investors, is tired of the hype. In fact, a Q1 2026 Nielsen survey found 75% of institutional investors care more about hard proof of operational efficiency and cost savings than they do about vague promises of future growth. The message is clear: a story built on small, verifiable wins is going to land much better. For instance, talk about how your AI supply chain tool cut shipping costs by 3% in the Southeast region, not how it’s going to “revolutionize global logistics.” These small, data-backed wins build real trust and show the tech actually works, which is what those skeptical execs want to see.
The “Unseen” ROI: Addressing Indirect Benefits
Part of the struggle with AI’s ROI is that some of its biggest wins are indirect and hard to pin on a P&L statement. Think about an AI tool that automates grunt work, improving employee satisfaction and lowering turnover. That’s a huge win, but it doesn’t show up as direct revenue. According to a HubSpot report this year, tech-driven improvements in employee retention can save a company an average of $15,000 per employee in recruiting and training. That’s a very real, if indirect, return on investment. Public relations professionals have to get good at telling this side of the story. It means partnering with HR and Ops to put numbers on things like lower employee churn or faster onboarding times. When you present these “softer” savings next to the direct financial gains, you build a much stronger, more complete case for the AI spend.
Proactive Transparency: The Antidote to Doubt
With so much doubt around AI revenue, PR teams have to get proactive and transparent. Just waiting for the tough ROI questions on the quarterly earnings call is a recipe for disaster. Instead, companies should be giving regular, detailed updates on AI progress, even when the results are small. A 2025 investor relations study showed that firms giving monthly or bi-monthly progress reports (even preliminary ones) had 10% higher investor confidence than those just sticking to quarterly updates. This isn’t about faking wins. It’s about being open about the entire process, including the challenges. You could even publish a post explaining how an AI model flopped on one campaign, what you learned, and how that led to a 5% lift on the next one. That kind of honesty builds massive credibility and turns a conversation about doubt into one about steady, iterative progress.
Dealing with AI revenue doubts means changing how we talk about AI, period. The era of selling vague, futuristic dreams is finished. To maintain confidence and keep the investment flowing, the PR narratives have to be built on a foundation of measurable outcomes, transparent reporting (wins and losses), and a clear accounting of those valuable indirect benefits.
What specific metrics actually prove AI ROI?
Focus on metrics that hit the bottom line. Things like reductions in customer acquisition cost (CAC), better lead conversion rates, direct operational savings (like a 5% cut in processing time), or a quantifiable jump in employee productivity.
How do you talk about AI failures without scaring off investors?
Frame failures as learning experiences. Be specific about how the “bad” data from the failed attempt helped you build a better version 2.0. Showing that iterative process proves you’re adaptable and committed to getting it right, which builds more trust than pretending everything works perfectly the first time.
How important is internal comms for a strong AI PR strategy?
It’s absolutely essential. Your employees are on the front lines of any AI implementation. If you share internal wins with them, explain the strategy, and show how a new tool makes their job better, they can become your most believable advocates and strengthen your external story.
Should we get specific about the *type* of AI we’re using?
Yes, it adds much-needed clarity. Explaining that you’re using generative AI for content creation versus predictive AI for sales forecasting helps people understand exactly what the tool does and what value to expect. It prevents you from making broad, fuzzy claims about “AI”.
How often do we need to report on AI progress?
Investor relations research suggests that monthly or bi-monthly updates work best. Even if the progress is small and the numbers are preliminary, that regular communication builds more confidence than waiting for the big quarterly report. It shows you’re on top of it.
