At a Glance
- From healthcare diagnostics to cybersecurity, AI technologies are revolutionizing workflows and creating new possibilities.
- As AI expands, companies must implement proper data governance, oversight, and ethical guidelines.
- The rise of "digital coworkers" and agentic AI is reshaping business models and team structures.
July 16 is AI Appreciation Day. The day is set aside to honor the transformative impact of artificial intelligence across industries and daily life. The day was established in 2021 by A.I. Heart to recognize how AI technologies have revolutionized everything from healthcare diagnostics to navigation apps and smart assistants.
The goal is to acknowledge AI's positive contributions while encouraging conversations about ethics and responsible development. As AI sinks deep roots into our daily lives – helping doctors interpret medical scans, powering recommendation systems, and enhancing cybersecurity – we need to manage AI technologies responsibly. That means balancing AI advancements with thoughtful implementation.
Taking a deep dive into AI and everything it means, we’ve gathered a wide range of comments from leaders across the world of AI technology.
Freddy Kuo, chairman of Luminys, chairman of SYNC ROBOTIC, and special office executive assistant at Foxlink
AI Appreciation Day is a moment to recognize the industry innovation and advancements in AI and robotics that are reshaping industries. From autonomous inspection systems and mobile robotic platforms to smart security solutions, robotics powered by AI is accelerating a new era of technology that is improving our daily lives.
These breakthroughs reflect a growing ecosystem of collaboration among technology leaders, researchers, and developers who are working together to solve real-world challenges through intelligent, adaptive machines. Today, we celebrate not just the technology but the vision, ingenuity, and dedication behind it.
Matt Garst, federal expert at Mendix
In the world of application development, every day is AI appreciation day. But as AI-produced code is leveraged more widely, it's important to consider a few key principles to avoid faulty results and maximize ROI on these major investments.
Quality in is quality out, and data must be sourced ethically and from a variety of origins to ensure a diverse dataset. This helps minimize repetition and reduce bias. AI agents must be actively monitored; the worst thing you can do is “set it and forget it.” The modern Software Development Life Cycle requires developers to shift their focus from builders to strategic orchestrators, guiding automation tools effectively.
Upskilling the existing workforce is non-negotiable. While internal AI use can be a polarizing topic, failing to capitalize on this technology now could leave organizations quickly falling behind. Fortunately, there’s a wealth of resources available, many of them are free.
AI analytics
Jimmy Mesta, co-founder and CTO of RAD Security
Security teams use stacks that generate thousands of signals a minute across dozens of tools. It’s no longer possible to define every relationship between those signals with rules alone. AI is now actually the only way teams can keep up. Instead of using clumsy rules that keep breaking, AI can spot patterns, connect events across multiple parts of the security stack, and take action fast enough to matter. It’s basically necessary to use AI for at least some of these tasks, if you want a lean security team to continue to function at scale with a mature stack.
Josh Mason, CTO of RecordPoint
At the core of the solution is data. Companies need to focus on locating and understanding the sensitive customer data they have, and their obligations when it comes to data retention and minimization, access and security. They can accelerate AI adoption with a risk-based, data-centric approach to identifying fit for purpose data for model training, ensuring that the only data that goes into an AI model is that which does not contain confidential or sensitive information.
Autonomous AI
Derek Collison, CEO and founder of Synadia
As we take the time to reflect on how quickly agentic AI has evolved over the past year and think about the massive potential benefits it can deliver, it’s also important to think about how users can improve how they communicate with AI agents to avoid Agentic AI failures. While many people complain that their AI "doesn’t work," agents often fail because of poor direction from the user. 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 when interacting with their AI (whether written or spoken).
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. Additionally, implementing a closed, deterministic feedback loop is also a great way to interact with AI agents.”
Jawahar Sivasankaran, president of Cyware
AI agents are redefining cyber threat intelligence operations. Our industry’s challenge was never a lack of intelligence but the capacity to operationalize it. On this AI Appreciation Day, we highlight Agentic AI as the ultimate force multiplier, transforming data overload and complexity into a decisive advantage and enabling teams to act with clarity, speed, and precision.
These agents move beyond static automation, ushering in a new era of intelligent, adaptive defense where enrichment and triage happen seamlessly and insights are never lost. Their power comes from deep contextual understanding, collaborative reasoning, and the ability to work with human analysts and each other. The infusion of agentic AI into threat intelligence platforms marks a shift from fragmented tools to unified, context-aware operations that elevate human decision-making and deliver resilient, synchronized cyber defense.
AI is revamping the business model
Josh Mason, CTO of RecordPoint
A massive AI transformation is underway across all levels of the enterprise, from engineers vibe-coding whole applications in days, not weeks, to executives streamlining communication and strategy. With the rise of agentic AI, these models are becoming more embedded into our working and personal lives. Businesses that prioritize governance, with a focus on data at the core, will be those best positioned to benefit from this transformation.
The companies that will experience success with this transformative technology will be those who rethink their entire business model and governance approach. Signing up for a company Copilot or Chat GPT license isn’t enough, and it doesn’t manage your risk. You have to make sure you govern your data and use the technology responsibly and ethically, in a way that benefits your customers and employees.
The new army of digital workers
Ron Reiter, CTO and co-founder of Sentra
Our coworkers aren’t just the people we sit next to in conference rooms or on Zoom calls anymore. As AI systems grow more capable, the line between tool and teammate is starting to blur. With agentic AI on the rise, we’re entering a new phase where software doesn’t just support decisions, it makes them. It takes action. It moves fast.
That should give all of us pause. We’re now working alongside digital coworkers we didn’t hire, don’t fully control, and who never take a break. Organizations are already struggling with insider threats from humans. What happens when AI agents access sensitive data, interact with critical systems, and operate at a pace no human can match? Mistakes are harder to catch, and when things go wrong, they escalate quickly.
AI needs oversight, guidance, and accountability. If we’re going to work alongside machines, we need to make sure they earn our trust, not just our admiration.
DeeDee Kato, VP of corporate marketing at Foxit
AI Appreciation Day is more than a nod to clever algorithms - it’s a recognition that we’ve crossed a line. AI isn’t just something happening ‘out there’ anymore. It’s in our everyday workflows, our inboxes, our documents – and the businesses leaning into it are starting to pull ahead. You can feel the shift: the companies still managing documents manually are beginning to look like they’re moving in slow motion.
AI is giving knowledge workers a real advantage. It's summarizing, redacting, translating, and understanding in seconds, instead of spending countless hours painfully combing through contracts, reports, or research papers. But it’s about working smarter, with fewer mistakes and more confidence, not just working faster. In our space, the companies that are quietly embedding AI into the way people handle documents aren’t just future proofing, they’re setting the new standard.”
Building AI infrastructure
Richard Copeland, CEO of Leaseweb USA
Artificial Intelligence Appreciation Day is a reminder of just how quickly innovation can change the landscape of entire industries. However, despite the breakthroughs in large language models, computer vision, and real-time analytics, one foundational truth remains: none of it works without robust infrastructure. Too often, organizations get stuck investing time and capital into building physical environments when their real competitive edge lies in algorithm development and application design. For the most forward-thinking teams, I’m seeing a shift in mindset. They recognize that offloading the burden of physical infrastructure is critical in order to stay focused on what truly moves the needle: the models, the insights, and the end-user experience.
This approach does more than save time; it unlocks speed, agility, and experimentation. When AI teams can access scalable computers and storage exactly when needed without being hindered by procurement delays or legacy systems, they're able to iterate faster and deploy smarter. A much shorter path from proof of concept to production is the result. Of course, in a competitive AI landscape, that agility is often the difference between a promising idea and a market-defining product. We’re entering an era where infrastructure is no longer a blocker. It’s a launchpad.
Roger Brulotte, CEO of Leaseweb Canada
As AI moves from curiosity to a critical business tool, we’ve watched the demands behind the scenes skyrocket. What once powered research labs now drives customer service, diagnostics, logistics, and more. Of course, progress at this pace presents significant challenges. Take the constant push to scale, meet regulatory demands, manage budgets, and deliver results. Add to that, an environment that never slows down. This is forcing organizations to take a moment to step back and ask a more thoughtful question: How do we grow in a way that’s not just fast, but smart, sustainable, and aligned with what we actually need?
This is where the real shift is happening… Forward-thinking teams are stepping back to focus on what really matters. In other words, they aren’t trying to wedge their workloads into inflexible systems. They’re seeking infrastructure that meets them where they are and grows with them. For some, that might look like adding more computer power right now. Still for others, it’s about tightening security or being ready to scale globally when the time comes. Bottom line, business and technology leaders are done chasing technical specs for their own sake. It's time now to build environments that leave room to adapt, grow, and evolve with purpose. In an AI-powered world, that kind of flexibility is everything.”
The need for AI guidance and guardrails
Rick Caccia, CEO and co-founder at WitnessAI
AI is already here; employees are using it, and enterprises are racing to adopt it. But like any high-performance machine, AI needs more than just power—it needs control.
Think of AI as a sports car: the engine is powerful, but without brakes and steering, it’s a liability. AI governance isn’t about slowing down progress—it’s what enables us to move faster, with confidence.
Our latest survey shows 63% of employees are already using AI to boost productivity. But most say they lack clear guidance. That’s a gap and a risk. Enterprises must meet this moment with clarity—gaining full visibility into how employees use AI and establishing control without hindering progress.
The AI revolution isn’t coming. It’s here. And we have a choice: bolt on safety later or build it into the frame. Let’s choose the latter and make every intelligent decision a secure one.
Niraj Tolia, CTO at Veeam
AI Appreciation Day is a reminder of its greatest dependency: clean, available, and protected data. AI can only deliver results if its data foundation is resilient. If this foundation is compromised or inaccessible, AI initiatives will grind to a halt.
Organizations are generating a goldmine of data; the real challenge is ensuring it’s always available and secure. We need to ensure that this data is not locked behind walled gardens and that it is always secured. That’s why data resilience must be a board-level priority, not just innovation alone.
To truly lead in AI, we must build with resilience, openness, and data portability at the core. If we want to keep AI advancing, we need to guarantee that the data fueling it at the foundation is always protected, always accessible, and always ready for action.