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, Delete” in Harvard Business Review. His thesis was radical and prescient: companies should eliminate work and processes that do not create value, rather than simply automating inefficiencies with technology.
Put another way, 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 inculcating bad habits, should be used selectively and strategically to help create value. His book on the subject, Corporate Reengineering: A Manifesto for Business Revolution, it was later rated as one of the 25 most influential management books by Time magazine and influenced leading time management theorists such as Peter Drucker and Tom Peters. By 1993, 60% of Fortune 500 companies were said to be engaging in Business Process Reengineering (BPR) initiatives.
Business Process Reengineering Cycle
Review of the basic components of BPR
You might wonder what a 30-year-old management theory has to do with what’s 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.
- Using disruptive technologies to challenge traditional work approaches.
I would suggest that 30 years later, these pillars resonate in the context of generative AI, large language models (LLM) and AI-driven agents, as they collectively help organizations of all shapes and sizes deliver customer value in ways they never imagined before. These technologies have the potential to achieve what Hammer and his contemporaries envisioned—on 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, customer and employee performance.
Automation vs AI Workflow vs AI Agents
In fact, McKinsey estimates that the AI generation could enable the 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 almost daily releases of new AI offerings, it is clear that the AI generation is poised to explode as BPR did and trigger a second wave of business process reinvention that will fundamentally reshape organizations. inside and outside.
But like BPR in the 1990s, harnessing the potential of AI is not 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 remarkably simple:
- What is your AI strategy?
- Where will you start with AI?
- How big will your investment be?
While these questions may seem basic, facing them reveals a cascade of deeper and more complex considerations. For example, asking about an AI strategy isn’t just about defining a technology roadmap—it’s about reevaluating your organization’s core mission and its approach to creating customer value. Similarly, determining where to start involves identifying not only low-hanging fruit, but also long-term opportunities that align with your strategic objectives. And when it comes to investment, it’s not just a matter of dollars – it’s about investing in the skills, culture and infrastructure that will enable sustainable success.
Applying BPR Principles to AI
Hammer’s principles of BPR provide 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 take full advantage of AI, leaders must think beyond incremental improvements and embrace radical change. This starts with reimagining a company as a native AI company – starting with why they exist, what they do to deliver customer value, and how their products and services deliver that value. Building a truly indigenous AI company requires reimagining and redesigning all core business processes using today’s generative capabilities.
This is more than technology adoption, it is a fundamental change that can fundamentally change the face and nature of a company. For example, AI can allow a company to shift from selling products to delivering results or insights. This change may require redesigning supply chains, retraining employees, and redefining customer relationships.
When tackling AI adoption, it’s essential to start with high-impact, manageable use cases. Hammer’s emphasis on targeted and impactful change still rings true today. Leaders need to identify areas where AI can deliver quick wins – whether it’s automating repetitive tasks in finance, optimizing marketing campaigns or improving customer service with AI agents.
Since you can’t do everything at once, determine which part of your organization will benefit most from one of three strategies—deploying simple automations, integrating AI into the workflow, or putting AI agents to work along with human employees. Each of these alternative approaches offers different opportunities to learn, iterate, and build momentum toward an end goal of a broader transformation, not just to make a process cheaper and faster.
- Build AI competency across your organization.
Adopting AI at scale isn’t just a technical challenge—it’s a cultural challenge. Hammer recognized that the human and organizational dimensions are critical to successful change. For AI initiatives to succeed, employees at all levels must understand, embrace and feel confident using these technologies.
This means investing in education and training, fostering a culture of experimentation and addressing fears around 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 said, “The true 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 improvement.
A new era of reinventing business processes
Hammer’s call to “delete, not automate” feels even more urgent today. Artificial intelligence is poised to reshape industries in ways that were unimaginable 30 years ago. But the way forward requires more than technology; it requires leadership, vision and a willingness to challenge the status quo using AI.
For companies and their leaders who missed the BPR wave in the 1990s, this moment represents a second chance. The opportunities that AI presents—to drive growth, improve efficiency, and deliver new customer 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 re-imagine, re-engineer and reinvent. Don’t wait another 30 years.