University of Kwazulu-Natal

The Emerging Agentic Enterprise How Leaders Must Navigate A New Age Of

Bonisiwe Shabane
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the emerging agentic enterprise how leaders must navigate a new age of

The 2025 Artificial Intelligence and Business Strategy report, from MIT Sloan Management Review and Boston Consulting Group, looks at how organizations that are adopting agentic AI are gaining advantage while facing four distinct tensions. The research and analysis for this report was conducted under the direction of the authors as part of an MIT Sloan Management Review research initiative in collaboration with and sponsored by Boston Consulting Group. Executives have long relied on simple categories to frame how technology fits into organizations: Tools automate tasks, people make decisions, and strategy determines how the two work together. That framing is no longer sufficient. A new class of systems — agentic AI — complicates these boundaries. These systems can plan, act, and learn on their own.

They are not just tools to be operated or assistants waiting for instructions. Increasingly, they behave like autonomous teammates, capable of executing multistep processes and adapting as they go. Notably, 76% of respondents to our global executive survey say they view agentic AI as more like a coworker than a tool. For strategists, agentic AI’s dual nature as both a tool and coworker creates new dilemmas. A single agent might take over a routine step, support a human expert with analysis, and collaborate across workflows in ways that shift decision-making authority. This tool-coworker duality breaks down traditional management logic, which assumes that technology either substitutes or complements, automates or augments, is labor or capital, or is a tool or a worker, but not all at...

Organizations now face an unprecedented challenge: managing a single system that demands both human resource approaches and asset management techniques. The separation of technology and strategy inside most organizations exacerbates this challenge. Technology executives focus on technology issues, making pilot, vendor, or infrastructure decisions. Strategic executives focus on markets, competition, and people. But agentic AI makes that separation untenable. It simultaneously influences the design of processes, the structure of roles, the allocation of decision rights, and the culture of accountability.

BOSTON—Agentic AI—systems that can plan, act, and learn on their own—is being embraced by organizations at a speed that outpaces the adoption of traditional and generative artificial intelligence. In less than two years, 35% of companies are already exploring agentic AI, with another 44% of companies planning to deploy it soon. However, few organizations have developed the management frameworks necessary for redesigning their workflows, governance models, investment planning, and talent strategies to keep up with this unprecedented pace. These are among the findings of the ninth annual global research study on AI and business strategy released today by MIT Sloan Management Review and Boston Consulting Group (BCG). Titled The Emerging Agentic Enterprise: How Leaders Must Navigate a New Age of AI , the report draws from a survey of 2,102 executives across 21 industries and 116 countries, as well as interviews... “Historically, we had a nice, clean separation between technology and people, with management processes designed around that distinction.

But agentic AI is neither a tool nor a teammate — it’s both and thrives in that blur. The organizations that will succeed are those that recognize agentic AI’s dual nature as a feature, not a bug,” said report coauthor Sam Ransbotham, an analytics professor at Boston College. Unlike earlier technologies, agentic AI systems are more than just tools to be operated or assistants waiting for instructions. Increasingly, they behave like autonomous teammates, capable of executing multistep processes and adapting as they go. Notably, 76% of the executives surveyed view agentic AI as more like a coworker than a tool. “Agentic AI has the power to transform entire workflows and challenge existing business processes.

The organizations that will succeed are those that put in the effort to reimagine their processes and not just force-fit agentic AI into existing ones,” said Shervin Khodabandeh, BCG managing director and senior partner,... Executives are fond of quoting hockey great Wayne Gretzky, who is credited with saying: “I skate to where the puck is going to be, not where it has been.” This is sound business advice... But that puck is moving a whole lot faster than it used to as agentic AI rapidly evolves. This article is a collaborative effort by Alex Singla, Alexander Sukharevsky, Lari Hämäläinen, Oana Cheta, Olli Salo, Pallav Jain, Raghav Raghunathan, Sandra Durth, Stéphane Bout, and Vito Di Leo, representing views from QuantumBlack, AI... The call to move faster may seem tone deaf as CEOs and their senior teams struggle to see bottom-line value from early gen AI investments. Developing and scaling gen AI use cases have proven frustratingly challenging.

Some executives remain unconvinced that AI agents will have a significant impact—at least in the short term—and have stepped back from their investments.1“Gartner predicts over 40% of agentic AI projects will be canceled by... As CEOs navigate the uncertainty, it is worth acknowledging both the pace and potential scope of the change that is happening. AI agents—software systems built with gen AI that have the ability to plan, act, remember, and learn to achieve predefined outcomes autonomously—are evolving quickly and, as they mature, could completely change how companies are... In fact, this “trough of disillusionment” period, as John Lovelock of Gartner recently called it,2“Welcome to the AI trough of disillusionment,” Economist, May 21, 2025. is an opportunity for executives to jump ahead of their competitors. AI agents are becoming more human-like in the kinds of tasks they can do and the way people interact with them.

These features democratize AI in a way prior technologies haven’t and underscore agents’ potential to affect a broad set of activities. The increasing possibilities of gen AI—the foundational capability that enables AI agents—are fueled by four mutually reinforcing trends: Chatbots once symbolized digital transformation — those polite text boxes on corporate websites and service portals promised to make support smarter and cheaper. The addition of generative AI (genAI) to the tools in recent years has made them seem more natural in conversations, but they’re still just automated answer engines. Now as 2025 comes to an end, traditional chatbots are beginning to look like relics of an earlier era. A new wave of agentic AI is taking shape: systems that not only converse but also reason, plan, and act within enterprise workflows.

These agents are not assistants that talk; they are digital colleagues that think. Across industries, companies are reengineering their operations to harness this new capability. They’re discovering that agentic AI isn’t simply an upgrade to chatbots — it’s a redefinition of how digital work gets done. Jesse Flores, founder and CEO of web development firm SuperWebPros, has watched this transition unfold firsthand. “Traditional chatbots,” he said, “were basically decision trees — if keyword X, then response Y.” They worked well for FAQs and appointment scheduling, but their world was bounded by the script. Even when connected to large language models such as GPT-5, most chatbots still lack deep knowledge of a company’s data or business context.

“They’re language-driven responders,” Flores explained. “They talk, but they don’t think or act.” If you find value in content like this, sign up for my Talent Edge Weekly newsletter. This new, in-depth report offers a range of considerations, strategies, and tactics for tapping the potential of agentic AI in organizations. While this 40-page report contains more insights than can be covered here, one theme stands out: AI adoption is racing ahead of strategy. Traditional AI adoption is at 72%, genAI at 70%, and agentic AI has reached 35%, with another 44% planning to deploy it.

The challenge is that AI is scaling faster than leaders are redesigning processes, decision rights, and workforce models. As a result, the authors note that competitive advantage won’t come from early access to agentic AI (because everyone will have it), but from stronger organizational design around it: how work is structured, how... The report also outlines tactics for making key decisions, such as determining when to bolt AI onto existing workflows for quick wins versus when to redesign entire processes around agentic capabilities. It notes that work design will shift from automating tasks to rethinking workflows; instead of asking “Where can we automate a step?” leaders will ask “Which processes should be rebuilt around human–AI collaboration?” The... As a bonus, here is a new article from McKinsey: HR’s Transformative Role in an Agentic Future. Want to stay informedabout Chief Human Resources Officer(CHRO) hires andpromotions?

Become amember of CHROs on the Go. DISCLAIMER: The views and opinions expressed on brianheger.com are solely my own (Brian Heger) and those of the original authors and do not represent the views or opinions of my employer. The next decade won’t be defined by incremental digital upgrades, but by a profound shift toward autonomous, adaptive, and self-optimizing systems powered by agentic AI. From my vantage point leading the AWS partnership for Capgemini across the Americas, I see this shift unfolding every day. Organizations have matured beyond isolated automation and Gen AI pilots. They now want AI that understands business intent, coordinates complex work, and improves continuously, AI that helps them move with speed, resilience, and clarity.

This is the promise of agentic AI: transitioning from simple task execution to autonomous value creation at enterprise scale. Agentic AI is reshaping the very core of how enterprises design their operations, deliver value, and respond to constant change. Instead of relying on fragmented systems and manual orchestration, organizations can now embed intelligence directly into their workflows. This transition creates a foundation where business goals, data, and decision-making are continuously connected. The result is an operating environment that adapts in real time, responds proactively rather than reactively, and evolves alongside shifting market dynamics. For enterprises navigating complexity, this marks the beginning of a more fluid, resilient, and future-ready way of working.

Agentic AI marks a shift from static processes to dynamic, goal-oriented systems that adapt in real time. Instead of isolated workflows, enterprises gain intelligent ecosystems, AI agents that reason, coordinate, and deliver outcomes across the organization. The result is a step-change in how companies operate, innovate, and compete. The agentic AI era is here, and it will reshape how businesses operate. The question is: Is your leadership team equipped to handle it? How quickly can you equip your leadership team and workforce with the capabilities to harness their power?

This isn’t just about integrating more automation; it’s about leading organizations through a paradigm shift where autonomous AI agents will increasingly define workflows, decision-making and competitive advantage. This necessitates a strategic focus on three core leadership skills, designed not just to future-proof individual careers, but to ensure the enduring resilience, transformation and innovative capacity of your entire enterprise. The Challenge: In the traditional IT landscape, leadership defines requirements and teams build to spec. In the Agentic Era, the “spec” becomes a high-level goal, and the “build” is largely executed by autonomous agents. Without effective guidance, these agents can stray, underperform or even introduce new risks. The skill: Leaders must transition from simply demanding outcomes to becoming Agent Architects capable of strategically designing agentic workflows.

This involves: They must also ensure there are “clear chains of responsibility for agent decisions” as highlighted by Salesforce. The artificial intelligence (AI) landscape is evolving rapidly, from systems that respond to predefined inputs to intelligent agents that can perceive, reason and act independently. This next wave, called agentic AI, is already redefining the blueprint for enterprise transformation. Its promise lies not just in automating processes but in enabling autonomous decision-making, continuous learning, and collaboration across digital agents—creating entirely new operating models for businesses. The foundation for agentic AI adoption is already being laid.

According to a recent Prosper Insights & Analytics survey, 33.5% of the general population already uses generative AI, with adoption rates even higher among business executives (43.6%) and employees (50.2%). More tellingly, research emerges as the top use case, with 51.3% of respondents using AI for generating summaries and providing relevant information—a clear precursor to the autonomous research and decision-making capabilities that define agentic... According to market.us, the market for agentic AI is projected to expand dramatically, with some estimates suggesting a CAGR range of 35% to 46%, potentially reaching as high as USD 196.6 billion by 2034. These aren't just impressive numbers. They represent a fundamental reshaping of competitive advantage across industries. While generative AI sparked curiosity and experimentation, agentic AI demands strategic intent.

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