AI’s Hidden Superpowers: Emerging Use Cases Every Exec Should Know
AI is everywhere—from marketing automation to legal contracts to content generation. But while headlines focus on copilots and chatbots, some of the most transformative use cases are flying under the radar.
We asked members of the Senior Executive AI Think Tank to name one emerging AI use case they believe is still underhyped—and to explain why business leaders should be paying closer attention. Their responses paint a picture of what’s possible when AI is used not just to move faster, but to think deeper, collaborate smarter, and solve harder problems.
“The most exciting uses of AI are helping teams think better together”
AI That Thinks With You, Not Just For You
Daria Rudnik, Founder and CEO of Aidra.AI, believes the real frontier isn’t individual productivity—it’s AI-powered group collaboration.
“Most tools today are built for speed,” she says. “But the most exciting uses of AI are helping teams think better together.” That includes AI that helps map out complex discussions, surfaces blind spots in group decisions, and connects dots across departments. “In fast-moving environments, it’s not just what you know—it’s what your team can figure out together,” she explains. “And the teams that learn to think with AI—not just use it—will be the ones that stay ahead.”
This sentiment is echoed in Atlassian’s 2024 AI Collaboration Report, which found a distinct difference in productivity improvements between those who simply used AI to complete routine administrative tasks versus those who treated it more as an expert advisor. Those who used AI to brainstorm solutions, not just complete tasks, reported a more significant return on their investment, in addition to time savings.
Strategic Pattern Recognition
Divya Parekh, Founder of The DP Group, says too many leaders are using AI as a tool for output—not insight.
“The real power is in sensemaking,” she explains. “AI can surface weak signals, compress insights across disciplines, and reveal patterns that executives miss when they’re moving too fast.” In her view, the real competitive edge lies not in speed, but in foresight. “Most leaders are still solving puzzles. They should be reading maps.”
“Executives can now compress months of analysis into days”
Smarter Research, Faster Strategy
Jim Liddle, Chief Innovation Officer of Data Intelligence and AI at Nasuni, sees huge potential in AI-powered research and insight synthesis. “Executives can now compress months of analysis into days,” he says. More than speed, it’s about quality: AI can spot non-obvious patterns, test ideas against real-time data, and translate noise into action.
“This is how companies move from reacting to anticipating,” he says. “For businesses drowning in information but starving for insight, this is the breakthrough.”
The truth is the human mind is limited in how many tasks it can perform at once. Past experiments involving multitasking found that an overwhelming majority of participants missed critical visual information when their attention was split. AI tools are not similarly constrained, which is why they are so well-suited for data analysis tasks.
Autonomous Data Cleanup
Roman Vinogradov, VP of Product at Improvado, flags AI’s role in back-end data governance as a game-changer. “AI’s glamor roles get all the attention, but some of the most powerful impact comes from invisible infrastructure,” he says.
Specifically: autonomous data mapping, taxonomy reconciliation, and cross-platform normalization. “This unlocks cleaner analytics, easier tool integration, and faster onboarding,” he notes. “And it reduces the cost of manual data prep—hugely.”
“AI workforce augmentation for middle-skilled roles is massively underutilized.”
AI-Augmented Teams
According to Gordon Pelosse, EVP at AI CERTs, the next big leap isn’t replacing workers—it’s enhancing them. “AI workforce augmentation for middle-skilled roles is massively underutilized,” he says. He sees strong ROI in giving analysts, coordinators, and technicians tools that reduce errors, automate repetitive steps, and improve decision-making.
“This improves both performance and satisfaction,” he adds. “It’s scalable, low-risk, and immediately valuable. Leaders should prioritize this in their workforce planning now.”
As the world becomes ever more interconnected, having a tool that can offer real-time language translation allows teams to more effortlessly troubleshoot issues that might still arise wherever they occur. In addition to pure translation services, AI tools can also help technicians evaluate sentiment. This can help to minimize the sort of costly cultural misunderstandings that have cost businesses millions in legal settlements, penalties, and stock valuation drops.
Privacy-Preserving Data Innovation
Sarah Choudhary, CEO of Ice Innovations, sees synthetic data generation as an untapped goldmine—especially in industries like healthcare and finance. “It enables model training without compromising real user data,” she explains.
This makes it easier to test safely, refine performance, and maintain compliance in sensitive sectors. “It’s innovation without the risk of exposure,” she says.
“It (AI) enables model training without compromising real user data”
Takeaways for Business Leaders
- Shift from speed to strategy. AI isn’t just for acceleration—it’s a tool for insight, foresight, and better group decision-making.
- Unlock hidden ROI. Don’t overlook AI use cases in infrastructure, research synthesis, or mid-level workforce support.
- Think behind the scenes. Back-end tools like data normalization and synthetic datasets can power innovation safely and quietly.
- Invest in collaboration. The future of AI is cooperative, not just assistive. Smart teams will think with AI.
- Prioritize augmentation over automation. Elevate your people with tools that make them better—not replace them.
While the world races to automate content, customer service, and code, the next wave of AI value lies beneath the surface. As these Think Tank leaders make clear, the future of AI isn’t just about doing things faster—it’s about thinking differently, acting sooner, and building smarter foundations.
Executives who look past the hype and invest in these under-the-radar use cases will be better equipped to lead not just with efficiency, but with vision. Because in 2025, the real AI edge isn’t what you automate—it’s how you anticipate.
