In 1990, Michael Hammer, a former professor of computer science at the Massachusetts Institute of Technology (MIT), published a game-changing article “Reengineering Work: Don’t Automate, Obliterate” in the Harvard Business Review. His thesis was both radical and prescient: companies should eliminate work and processes that do not create value, rather than simply automating inefficiencies with technology.
Said differently, Hammer wanted leaders to stop focusing on doing the wrong thing better – even with the use of technology – and start focusing on the right thing – accelerating the creation of value for customers. Technology, rather than entrenching bad habits, should be deployed selectively and strategically to aid in the creation of value. His book on this topic, Reengineering the Corporation: A Manifesto for Business Revolution, was later hailed as one of the 25 most influential management books by Time magazine and influenced leading management theorists of the time like Peter Drucker and Tom Peters. By 1993, 60% of the Fortune 500 companies were reportedly engaging in Business Process Reengineering (BPR) initiatives.
Revisiting BPR’s Core Components
You may be wondering what a 30-year old management theory has to do with what is happening in today’s AI world. My answer: A lot.
Hammer’s BPR framework rested on three pillars:
- Fundamental rethinking and radical redesign of business processes to achieve dramatic improvements in cost, quality, service, and speed.
- Envisioning new work strategies, designing processes from the ground up, and managing complex technological and organizational changes.
- Leveraging disruptive technologies to challenge traditional approaches to work.
I would suggest that 30 years later, these pillars resonate in the context of generative AI, large language models (LLMs), and AI-driven agents as they collectively help organizations of all shapes and sizes deliver customer value in ways they never previously imagined. These technologies have the potential to achieve what Hammer and his contemporaries envisioned—at an even greater scale. This isn’t just theoretical either, as a recent article by Rakesh Gohel outlines three different automation approaches for improving corporate, customers and employee performance.
Automation vs AI Workflow vs AI Agents
In fact, McKinsey estimates that gen AI could enable automation of up to 70 percent of business processes by 2030, adding trillions of dollars in value to the global economy. Further, based on the breakneck pace of near-daily releases of new AI offerings, it is clear that gen AI is poised to explode as BPR did and trigger a second wave of business process reinvention that will radically reshape organizations inside and out.
But just like BPR in the 1990s, harnessing AI’s potential isn’t about rushing to automate everything. It’s about rethinking how value is created and delivered—and doing so thoughtfully, strategically, and sustainably.
The Big Questions Leaders Should Ask
At first glance, the questions organizations need to ask to embark on this journey seem deceptively simple:
- What is your AI strategy?
- Where will you get started with AI?
- How big will your investment be?
While these questions might appear basic, grappling with them reveals a cascade of deeper, more complex considerations. For example, asking about an AI strategy isn’t just about defining a technological roadmap—it’s about reevaluating the core mission of your organization and its approach to creating customer value. Similarly, determining where to begin involves identifying not only the low-hanging fruit but also the long-term opportunities that align with your strategic objectives. And when it comes to investment, it’s not simply a question of dollars—it’s about investing in skills, culture, and infrastructure that will enable sustained success.
Applying BPR Principles to AI
Hammer’s principles of BPR offer a useful framework for navigating this complexity. Here’s how organizations can apply them to their AI journeys:
- Re-envision your organization’s purpose and processes.
To fully capitalize on AI, leaders need to think beyond incremental improvements and embrace radical change. This starts with reimagining a company as an AI native company – starting with why they exist, what they do to deliver customer value, and how their products and services deliver that value. To build a true AI native company requires reimagining and redesigning all core business processes using today’s generative capabilities.
This is more than adopting technology, it’s a fundamental shift that could radically change the face and nature of a company. For example, AI might allow a company to move from selling products to delivering outcomes or insights. This shift could require redesigning supply chains, retraining employees, and redefining customer relationships.
- Start small, think big.
When tackling AI adoption, it’s essential to begin with high-impact, manageable use cases. Hammer’s emphasis on targeted, impactful changes holds true today. Leaders should identify areas where AI can deliver quick wins—whether it’s automating repetitive tasks in finance, optimizing marketing campaigns, or enhancing customer service with AI agents.
Given you can’t do everything at once, determine which part of your organization will benefit the most from one of three strategies – setting up simple automations, integrating AI into workflow, or deploying AI agents to work alongside human employees. Each of these alternative approaches offers different opportunities to learn, iterate, and build momentum towards an end goal of broader transformation, not just making a process cheaper and faster.
- Build AI competency throughout your organization.
Adopting AI at scale isn’t just a technical challenge—it’s a cultural one. Hammer recognized that human and organizational dimensions are critical to successful change. For AI initiatives to succeed, employees at all levels need to understand, embrace, and feel confident using these technologies.
This means investing in education and training, fostering a culture of experimentation, and addressing fears about job displacement. Employees should see AI not as a threat but as a tool that empowers them to focus on higher-value tasks and creative problem-solving. As Marcel Proust famously said, “The real voyage of discovery consists not in seeking new landscapes but in having new eyes.” True to this quote, leaders must foster a culture where AI is viewed through the lens of abundance and enhancement.
A New Era of Business Process Reinvention
Hammer’s call to “obliterate, not automate” feels even more urgent today. AI is poised to reshape industries in ways that were unimaginable 30 years ago. But the path forward requires more than technology; it requires leadership, vision, and a willingness to challenge the status quo using AI.
For companies and their leaders that missed the BPR wave in the 1990s, this moment represents a second chance. The opportunities AI presents—to drive growth, improve efficiency, and deliver new soyrces of customer,er value—are unprecedented. But so are the challenges. Success will require leaders to revisit Hammer’s insights and adapt them for a new era of AI driven reinvention.
Now is the time to reimagine, reengineer, and reinvent. Don’t wait another 30 years.
This post was originally published on here
