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Title: Trust and governance in the shift to agentic transformation
Description: I recently had an unsettling rideshare experience. Let me paint a visual picture. You have a Tesla doing its self-driving thing, a guy just sitting in the driver’s seat “supervising,” and a terrified human (me) in the backseat looking on in horror.Finally, I said, “Please keep your hands on the wheel when you’re driving me, OK?”Tesla’s autonomous functionality might be safe, but I don’t have enough trust yet to allow a Tesla to get me from Point A to Point B without a human steering it.There’s a parallel between self-driving cars and the current perceptions of AI and agents. You might be comfortable letting one of these automobiles make a simple right-hand turn, but turning left to cross through busy traffic? Probably not so much.We’re in the early days of agentic transformation, which describes the shift from traditional software to a more autonomous enterprise that relies on software that can act independently. Businesses are eager to embed agents in processes to make operations more efficient. Yet we’re in a remarkably similar place to autonomous vehicles with our level of trust, or lack thereof.Implementing simple agentic pilot use cases are one thing. But yielding control of critical workflows is another.WHAT RESEARCH TELLS USThis trust gap isn’t just a hunch on my part. It’s backed by respected research.In a recent KPMG International study of more than 48,000 people in 47 countries, 66% said that while they use artificial intelligence, 54% were unwilling to trust it. A McKinsey & Company report cited something similar, calling it the GenAI paradox. It found that almost eight in 10 companies use generative AI, but the same number has not seen any significant bottom-line impact. This is why the biggest AI challenge isn’t technical, the report stated. Instead, “It will be human: earning trust, driving adoption, and establishing the right governance to manage agent autonomy and prevent uncontrolled sprawl.”AI adoption is happening, but it’s not happening with great confidence. Every business leader should also think about a Pew Research Center study that found a vast chasm between the views of AI experts and the general public. The public is far less optimistic and enthusiastic about the technology.Bridging this skepticism divide will be the difference between success and failure for businesses as they “agentify” their operations.So, we still don’t fully trust AI to make meaningful decisions for us. We’ve all heard the stories of AI hallucinations and businesses rolling out initiatives that, in hindsight, weren’t ready for prime time. Caution is not the same thing as moving slowly. That said, the companies that figure out how to adeptly use agents in their businesses sooner will be the ones that move faster, execute smarter, and operate leaner.Building trust is the key that unlocks it all.WHY TRUST IS THE HARD PARTOf course, the trust in technology issue predates AI’s arrival. I’ve worked in software for three decades. For a significant portion of that time, the focus has been on digital transformation to make businesses more efficient through digitizing processes. One of the biggest obstacles companies have long faced is a deep distrust of their data.Incomplete, inaccessible, or inaccurate data can fundamentally paralyze organizations. Businesses don’t know what to trust. When facing critical decisions that can impact their companies’ trajectory, some of the most intense leadership team discussions are whether they believe what the data tells them. I’ve been part of those conversations.Now, as we shift into agentic transformation, if you don’t get the data right, AI can make the problem 10 times worse. That’s because AI models and agents use the data available as fuel to make decisions and generate outputs based on probabilities and likelihoods in a “black box” environment that can lack transparency. Because AI responses and actions are based on those probabilities, it will never be 100% accurate. (Much like humans, by the way.) But AI can be made as trustworthy as possible. It’s all predicated on:Accurate data.Access to information.Without setting a strong foundation for managing data and fully connecting systems so that information moves where needed, the conviction required to support your AI initiatives will be lacking. You’ll understandably have doubts about the actions that agents are taking within your organization and externally on behalf of your business.WHAT EVERY LEADER SHOULD CONSIDERChange only happens at the speed of trust. If we believe in something, we’ll use it. Building confidence in AI models and agents requires control and governance. It starts with the foundation I mentioned: well-managed data and well-integrated systems. Solving the age-old “garbage in, garbage out” problem of poor data is a crucial first step. It will give AI what it needs to make more accurate and responsible decisions.Then there are the agents themselves. We’ve reached a point where every organization can build agents, and every vendor is making them part of their products. But something else is more essential—managing them.You need to know about every agent in your operations. You’ll need visibility into what they’re doing and how they’re performing their assigned tasks. If they’re not acting as expected, you must be able to fix the issue quickly.These guardrails are the backbone upon which trust is nurtured as this new agentic world evolves and matures. For leaders, this requires striking the right balance between championing speed and responsible innovation in ways that enable AI to enhance efficiency while amplifying human capability. That’s because human interactions—helping customers, managing employees, and so on—will always be those more challenging “left-hand turns” where we want people to make decisions requiring empathy and judgment.Just as we’re moving toward a self-driving car that inspires unequivocal trust, we’re also on a path to metaphorically creating the self-driving enterprise with agents. For now, though, most of us aren’t yet willing to take our hands off our business’s steering wheel.Agents have to earn that kind of trust through governance.Steve Lucas is chairman and CEO of Boomi.
https://www.fastcompany.com/91419645/trust-and-governance-in-the-shift-to-agentic-transformationTrust and governance in the shift to agentic transformation.
📌 Ask AII recently had an unsettling rideshare experience.
📌 Ask AILet me paint a visual picture.
📌 Ask AIYou have a Tesla doing its self-driving thing, a guy just sitting in the driver’s seat “supervising,” and a terrified human (me) in the backseat looking on in horror.
📌 Ask AIFinally, I said, “Please keep your hands on the wheel when you’re driving me, OK?”Tesla’s autonomous functionality might be safe, but I don’t have enough trust yet to allow a Tesla to get me from Point A to Point B without a human steering it.
📌 Ask AIThere’s a parallel between self-driving cars and the current perceptions of AI and agents.
📌 Ask AIYou might be comfortable letting one of these automobiles make a simple right-hand turn, but turning left to cross through busy traffic? Probably not so much.
📌 Ask AIWe’re in the early days of agentic transformation, which describes the shift from traditional software to a more autonomous enterprise that relies on software that can act independently.
📌 Ask AIBusinesses are eager to embed agents in processes to make operations more efficient.
📌 Ask AIYet we’re in a remarkably similar place to autonomous vehicles with our level of trust, or lack thereof.
📌 Ask AIImplementing simple agentic pilot use cases are one thing.
📌 Ask AIBut yielding control of critical workflows is another.
📌 Ask AIWHAT RESEARCH TELLS USThis trust gap isn’t just a hunch on my part.
📌 Ask AIIt’s backed by respected research.
📌 Ask AIIn a recent KPMG International study of more than 48,000 people in 47 countries, 66% said that while they use artificial intelligence, 54% were unwilling to trust it.
📌 Ask AIA McKinsey & Company report cited something similar, calling it the GenAI paradox.
📌 Ask AIIt found that almost eight in 10 companies use generative AI, but the same number has not seen any significant bottom-line impact.
📌 Ask AIThis is why the biggest AI challenge isn’t technical, the report stated.
📌 Ask AIInstead, “It will be human: earning trust, driving adoption, and establishing the right governance to manage agent autonomy and prevent uncontrolled sprawl.
📌 Ask AI”AI adoption is happening, but it’s not happening with great confidence.
📌 Ask AIEvery business leader should also think about a Pew Research Center study that found a vast chasm between the views of AI experts and the general public.
📌 Ask AIThe public is far less optimistic and enthusiastic about the technology.
📌 Ask AIBridging this skepticism divide will be the difference between success and failure for businesses as they “agentify” their operations.
📌 Ask AISo, we still don’t fully trust AI to make meaningful decisions for us.
📌 Ask AIWe’ve all heard the stories of AI hallucinations and businesses rolling out initiatives that, in hindsight, weren’t ready for prime time.
📌 Ask AICaution is not the same thing as moving slowly.
📌 Ask AIThat said, the companies that figure out how to adeptly use agents in their businesses sooner will be the ones that move faster, execute smarter, and operate leaner.
📌 Ask AIBuilding trust is the key that unlocks it all.
📌 Ask AIWHY TRUST IS THE HARD PARTOf course, the trust in technology issue predates AI’s arrival.
📌 Ask AII’ve worked in software for three decades.
📌 Ask AIFor a significant portion of that time, the focus has been on digital transformation to make businesses more efficient through digitizing processes.
📌 Ask AIOne of the biggest obstacles companies have long faced is a deep distrust of their data.
📌 Ask AIIncomplete, inaccessible, or inaccurate data can fundamentally paralyze organizations.
📌 Ask AIBusinesses don’t know what to trust.
📌 Ask AIWhen facing critical decisions that can impact their companies’ trajectory, some of the most intense leadership team discussions are whether they believe what the data tells them.
📌 Ask AII’ve been part of those conversations.
📌 Ask AINow, as we shift into agentic transformation, if you don’t get the data right, AI can make the problem 10 times worse.
📌 Ask AIThat’s because AI models and agents use the data available as fuel to make decisions and generate outputs based on probabilities and likelihoods in a “black box” environment that can lack transparency.
📌 Ask AIBecause AI responses and actions are based on those probabilities, it will never be 100% accurate.
📌 Ask AI(Much like humans, by the way.
📌 Ask AI) But AI can be made as trustworthy as possible.
📌 Ask AIIt’s all predicated on:Accurate data.
📌 Ask AIAccess to information.
📌 Ask AIWithout setting a strong foundation for managing data and fully connecting systems so that information moves where needed, the conviction required to support your AI initiatives will be lacking.
📌 Ask AIYou’ll understandably have doubts about the actions that agents are taking within your organization and externally on behalf of your business.
📌 Ask AIWHAT EVERY LEADER SHOULD CONSIDERChange only happens at the speed of trust.
📌 Ask AIIf we believe in something, we’ll use it.
📌 Ask AIBuilding confidence in AI models and agents requires control and governance.
📌 Ask AIIt starts with the foundation I mentioned: well-managed data and well-integrated systems.
📌 Ask AISolving the age-old “garbage in, garbage out” problem of poor data is a crucial first step.
📌 Ask AIIt will give AI what it needs to make more accurate and responsible decisions.
📌 Ask AIThen there are the agents themselves.
📌 Ask AIWe’ve reached a point where every organization can build agents, and every vendor is making them part of their products.
📌 Ask AIBut something else is more essential—managing them.
📌 Ask AIYou need to know about every agent in your operations.
📌 Ask AIYou’ll need visibility into what they’re doing and how they’re performing their assigned tasks.
📌 Ask AIIf they’re not acting as expected, you must be able to fix the issue quickly.
📌 Ask AIThese guardrails are the backbone upon which trust is nurtured as this new agentic world evolves and matures.
📌 Ask AIFor leaders, this requires striking the right balance between championing speed and responsible innovation in ways that enable AI to enhance efficiency while amplifying human capability.
📌 Ask AIThat’s because human interactions—helping customers, managing employees, and so on—will always be those more challenging “left-hand turns” where we want people to make decisions requiring empathy and judgment.
📌 Ask AIJust as we’re moving toward a self-driving car that inspires unequivocal trust, we’re also on a path to metaphorically creating the self-driving enterprise with agents.
📌 Ask AIFor now, though, most of us aren’t yet willing to take our hands off our business’s steering wheel.
📌 Ask AIAgents have to earn that kind of trust through governance.
📌 Ask AISteve Lucas is chairman and CEO of Boomi.
📌 Ask AI🔁 What is the aéPiot Backlink Ping System?
Visit Original ContentaéPiot automatically sends a ping to your link every time a backlink page is accessed — by humans or bots.
The backlink pages look like:
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utm_source=aePiotutm_medium=backlinkutm_campaign=aePiot-SEO
You can detect this traffic using:
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aéPiot does not track or store any data. All analytics and traffic logs are only visible to you, so you can evaluate the true SEO and referral value of your aéPiot backlinks.
The Beneficial Role of Backlinks in SEO
Backlinks are one of the most important factors in search engine optimization (SEO). When your backlink is accessed—whether by real users, search engine bots, or crawlers—it signals to search engines that your site is valuable and trustworthy.
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The more your backlink is accessed—whether by humans or bots—the more it helps your site’s SEO performance. Consistent traffic through backlinks is a positive signal that can improve your search rankings and drive organic growth.
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