Industry Reflects on AI Appreciation Day
Happy AI Appreciation Day! While it may not warrant a regular entry on your yearly calendar, the rapid adoption of AI is something to take note of. This year, the event marks a good time to take note of how far we’ve come with AI and how far yet we have to go.
The first six months of the year have been marked by a rapid evolution of AI. From new reasoning models like Deepseek and new protocols like MCP, it seems we’re on the cusp of something big. So what’s holding AI back? According to Mike Capone, the CEO of data analytics firm Qlik, it’s not the technology or the talent, but trust.
“Only 28% of people would accept a prescription written solely by AI,” Capone said. “Just 24% would donate their health data, even though 52% would donate blood. That’s not a hesitation around technology–it’s a hesitation around confidence.”
Despite the vast amounts of attention lavished on AI, executives are feeling the strain of that trust gap, Capone says. How do we move forward to gain more trust?
“The answer isn’t more models. It’s clean, governed, explainable data that people can stand behind,” the Qlik CEO says. “AI only creates value when people believe in the outputs. If the foundation is fragile, the insight is too. Trust needs to be built in from the beginning. Without it, even the best AI won’t scale. It won’t be used.”
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Feeling frustrated by failed agent-human interactions? It may be tempting to blame the AI, but in some cases, it’s not the agent who’s at fault; it’s you.
“While many people complain that their AI ‘doesn’t work,’ agents often fail because of poor direction from the user,” says Derek Collison, CEO and Founder of edge AI company Synadia. “In reality, the AI likely did exactly what the user wrote, but not what they meant or intended because the instructions they were provided weren’t clear enough or lacked essential details.”
To avoid these challenges, users need to become better communicators, Collison says. “Providing more detail as early as possible helps agents become more attuned to a user’s style of communication, better at inferring what a user may be looking for based on previous interactions and ultimately improve the accuracy of future recommendations,” he adds. “Additionally, implementing a closed, deterministic feedback loop is also a great way to interact with AI agents.”
AI Appreciation Day should celebrate not only how far we’ve come, but also spotlight how far we still have yet to go with AI, says Spencer Kimball, CEO and co-founder of Cockroach Labs.
“We’re entering an era where machines don’t just think, they act autonomously and continuously. They don’t pause, and they don’t sleep. They operate at a frequency our systems were never built to withstand,” Kimball says. “So, the real constraint on AI isn’t model quality–it’s the fragility of the infrastructure beneath it. If we don’t modernize the legacy systems underneath, even the most powerful AI won’t perform when the architecture fails.”
Is AI a threat or am asset? In the context of security, it’s both, according to Vicky Bruce, the global capability manager for cybersecurity services at Rockwell Automation.
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“Nearly half of manufacturing leaders plan to use AI and machine learning (ML) for cybersecurity in the next 12 months,” Bruce says. As AI is being used to improve security posture, the same technology is also being used by attackers to automate intrusions and evade detection. Being proactive can make the difference between a minor alert and catastrophic downtime events that cost millions.
“This AI Appreciation Day, we must remember that ‘with great power comes great responsibility,’” Bruce continues. “The challenge is to harness AI’s potential yet remain vigilant, since AI can be a risk if not properly understood or trained.”
The maturation of AI has put it on the cusp of fundamentally reshaping business operations, says Raju Malhotra, chief product and technology officer for Certinia, which develops ERP software. So how can companies succeed with this new tech?
“The most effective AI strategies are built around real customer use cases and a layered approach that connects today’s practical applications with tomorrow’s transformative potential,” Malhotra says. “It starts with predictive AI making business decisions smarter and generative AI streamlining workflows.”
The most transformative addition is agentic AI, which more than 80% of companies are either actively deploying or planning to deploy. However, nearly 30% of companies expect to fail with their agentic AI projects.
“The reasons are clear: a lack of internal skills and fragmented data,” Malhotra says. “AI is only as effective as the data it can access across the customer lifecycle, and the right combination of human and digital talent can help customers scale capacity and capture new revenue.”
Companies should take a big picture view when it comes to AI and how it will impact human workers, according to Russell Lester, the president and CFO for Tropic.
“Everyone’s talking about AI like it’s either our savior or our replacement, but that misses what’s actually happening,” Lester says. “We’re at a tipping point where 86% of finance teams plan to scale AI by 2026, yet half of us are still figuring out the basics. The real story isn’t about robots taking jobs. It’s about AI handling the stuff that bogs us down so we can focus on decisions that actually move the business.”
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