What To Do When Machines Do Everything

1. AI Ushers in a New Era of Economic Growth

The bottom line? It's going to be all right. In fact, better than all right, because AI is about to usher in a new industrial revolution that, for those who manage it properly, will generate significant economic growth.

Fourth Industrial Revolution. Artificial intelligence (AI) is driving a new industrial revolution, characterized by economic dislocation and the rise of "systems of intelligence." This era promises significant economic growth for those who can harness the power of AI, algorithms, bots, and big data. The rise of AI is poised to transform how we are educated, fed, transported, insured, medicated, and governed.

From Stall to Boom. The economy is transitioning from a "stall zone" to a period of technology-fueled growth. This "digital build-out" will see the fruits of digital technology move from Silicon Valley to the entire economy, creating opportunities for established companies to leverage their industry knowledge with the power of new machines. The key is to understand the new machine and situate it in the right business model.

The Promise of AI. AI is not just about entertainment or convenience; it's about addressing societal ills and improving the pillars of our society. Driverless cars promise to save lives, AI can help feed the world by optimizing the food supply chain, and medical misdiagnoses can plummet with AI-enhanced diagnostic processes. This is "digital that matters," and it will be driven by big brains both inside and outside of Silicon Valley.

2. The Digital Build-Out Requires Mastering the Three M's

They understand today's new raw materials (big data). They have built and now operate the new machines. And, most important, they have surrounded these new machines with business models that generate remarkable growth and profitability engines while expanding the overall market.

Aligning the Three M's. Success in the digital economy requires aligning three key elements: raw materials (data), new machines (systems of intelligence), and business models. Established companies are well-positioned for the digital build-out because they possess market knowledge, products, and assets to instrument. The Three M's have to be integrated and aligned to create value.

The Three M's Defined.

• Raw materials: Data generated from IoT devices and instrumentation of people, places, and things.
• New machines: Systems of intelligence that combine hardware, AI software, data, and human input.
• Business models: Commercial models that monetize services and solutions based on systems of intelligence.

GE's Transformation. General Electric (GE) serves as an example of a company reconfiguring itself around the Three M's. GE is instrumenting its products, building an IoT management platform (Predix), and selling insights based on the data, opening up new lines of business. GE now has a software business earning more than $6 billion in revenue.

3. AI Will Reshape, Not Eliminate, Most Jobs

Will many jobs be “automated away” in the coming years? Yes. However, for the vast majority of professions, the new machine will actually enhance and protect employment.

Job Automation, Enhancement, and Creation. The impact of AI on the labor force will be threefold: job automation (12% of existing jobs at risk), job enhancement (75% of existing jobs altered), and job creation (13% net new jobs). The focus should be on understanding what the new machine can and cannot do and how it will impact the future of work.

Manual vs. Knowledge Labor. Manual labor and knowledge labor are not interchangeable, and their substitution by machines is different. Knowledge automation is not zero-sum; it allows for more throughput and mass customization that was impossible before systems of intelligence. The automation of knowledge assets is not just a matter of removing existing labor.

Jobs vs. Tasks. Most analyses fail to distinguish between "jobs" and "tasks." Jobs are composed of various tasks, some of which can be automated while others will never be automated. The new machine will change jobs, but it will not eliminate them completely.

4. Systems of Intelligence: The Anatomy of the New Machine

A system of intelligence combines software (algorithms, business rules, machine-learning code, predictive analytics), hardware (servers, sensors, mobile devices, connectivity), data (contextualized and real-time), and human input (often judgment or questions).

Defining Systems of Intelligence. A system of intelligence combines software, hardware, data, and human input to create value. These systems are characterized by software that learns, massive hardware processing power, and huge amounts of data. The new machine is rapidly becoming the cornerstone for companies that compete on knowledge.

Key Attributes of AI:

• Software that learns: Machine-learning software improves over time, recognizing patterns and finding hidden insights without explicit programming.
• Massive hardware processing power: Cloud computing enables hyper-powerful computers to be tied together for blazing-fast performance.
• Huge amounts of data: Data is the fuel of the new economy, providing the context for personalized and curated experiences.

Narrow AI is Key. The focus should be on narrow AI (ANI), which is purpose-built and business-focused on a specific task. ANI is a tool that provides the basis for all that can be explored in the coming pages.

5. Data: The Fuel Powering the New Machine

Data is the fuel of the new economy.

Data as the New Oil. Data is the primary raw material of the Fourth Industrial Revolution. Like oil, data needs to be "mined," "refined," and "distributed." However, data is a potentially infinite resource that can grow quickly in scale and value.

Managing the Data Supply Chain. Turning data into actionable insight requires establishing and managing a "data supply chain" across the business. This involves exploration and extraction (upstream), refining (midstream), and distribution (downstream). The middle step, the refining of data or turning it into meaning, will be the key competitive battleground.

Instrument Everything. The strategic question shouldn't be "What should we instrument?" but rather "What shouldn't we instrument?" Instrumenting all operations, products, and customer experiences is essential for gaining proprietary insights and competitive advantage.

6. Digital Business Models: Five Ways to Win

This is where many people get stuck. They start tumbling down existential wormholes: Will machines need us? Who will control the machines? Will machines act in the best interests of humanity? Again, these are great questions that prompt fascinating discussions, all of which we like having as much as the next person, particularly with a glass of red wine on hand. But these discussions don't help you know what to do.

The AHEAD Model. The AHEAD model outlines five distinct approaches for winning with systems of intelligence: Automate, Halo, Enhance, Abundance, and Discovery. These are five specific approaches for winning with AI, each with its own set of approaches and tactics.

The Five Approaches:

• Automate: Outsource rote, computational work to the new machine.
• Halo: Instrument products and people and leverage the data exhaust to create new customer experiences and business models.
• Enhance: View the computer as a colleague that can increase job productivity and satisfaction.
• Abundance: Use the new machine to open up vast new markets by dropping the price point of existing offers.
• Discovery: Leverage AI to conceive entirely new products, new services, and entirely new industries.

Hybrid Models. The winning business models will be hybrid—part physical, part digital. The challenge is to decide what goes where, what stays physical, and what goes digital.

7. Automation: The Foundation for Digital Transformation

Software Should Be Eating Your Core Operations.

Automation as a Means, Not an End. Automation is the initial step in each industrial revolution. It is a necessary "evil" for delivering at the "Google price." However, the next wave of automation will pave the way for invention and economic expansion through the four subsequent plays.

Targeting Core Operations. The best areas for automation are in the back and middle offices, including information technology, finance, human resources, claims processing, and customer service. These areas comprise an information supply chain that gathers, synthesizes, transforms, and distributes data.

Rules of the Road for Automation:

• Set a 25%-25% automation imperative (25% cost reduction and 25% productivity increase).
• Find process-automation targets with repetitive tasks, low demand for human judgment, and high volumes of data.
• Break through the "brass wall" by addressing the concerns of middle managers.
• Build a repeatable process to obliterate work.

8. Halo: Instrument Everything to Create New Value

Every “Thing” Is Now a Code Generator.

The Power of Code Halos. Instrumenting products and people and leveraging the data exhaust they generate (Code Halos) can create new customer experiences and business models. The race is on to win through instrumentation, and established companies are changing the rules of competition.

Three New Rules of Competition:

• Instrumentation is no longer elective; it is now core curriculum.
• Code is more valuable than things.
• Never turn them off.

Discovery Health's Success. Discovery Health in South Africa uses its Vitality platform to provide economic incentives to its members based on whether they participate in healthy behaviors. This demonstrates how instrumenting products and people can create new value propositions and customer intimacy.

9. Enhance: Amplify Human Performance with AI

You + New Tools = Enhancement.

The Power of Enhancement. The new machine can increase job productivity and satisfaction. Entire vocations, from sales to nursing to teaching, will be revolutionized with the power of computer-based enhancement. Workers will come to view the new machine as their trusted colleague.

Enhanced Jobs Are Protected Jobs. The vast majority of white-collar work will be made better with the new machines. The key is to identify the roles, processes, systems, and experiences that can be upgraded by newly available technologies.

Smart Robots Make Smarter Hands. The combination of "smart hands" and "smart robots" is becoming more visible all the time. The machine continually gets smarter, and so does the human.

10. Abundance: Unlock New Markets by Lowering Prices

Increasing Prosperity by Lowering Prices.

The Concept of Abundance. As prices go down, demand goes up. The new machine can be used to open up vast new markets by dropping the price point of existing offers.

Narayana Health's Example. Narayana Health (NH) in India is revolutionizing cardiac surgery by leveraging digital technology. By lowering the cost of heart surgery approximately a hundred-fold, NH now provides world-class heart surgeries to anyone in need.

Key Strategies for Abundance:

• Obsess about the start-up community.
• Kill your company (ask employees to identify ways to disrupt your existing business).
• Play the "tomorrow it's free" game.
• Manage your innovator's dilemma.
• Make like a maker.
• Think like a corner shop (new personalization).
• Apply digital Taylorism.

11. Discovery: Manage Innovation for the Digital Economy

Discovery Is Hard, but Not as Hard as Being Irrelevant.

The Importance of Discovery. Discovery, or blue-sky innovation, is both a catalyst for and an outcome of the AHEAD model. It is central to remaining relevant in the great digital build-out.

R&D Without AI Is No R&D At All. The new machine will be the platform of innovation. Once you are instrumenting, automating, tracking, and analyzing the core operations of your business and applying machine learning, innovation opportunities will be consistently unearthed.

Key Strategies for Discovery:

• Apply digital Kaizen (continuous, incremental improvements).
• Let hits pay for misses (manage a portfolio of initiatives).
• Leave the past behind (decommission legacy systems).
• Play the Wayback Game (understand how quickly technology changes).

12. Competing on Code: A Call to Action

Courage and Faith in the Future.

The Future Is Here. The digital build-out is here, and it's time to act. The new machines will continue to amaze, will be embedded most everywhere and in most everything, and will increasingly do more and more of the work people do today.

Align the Three M's. To win in the digital economy, you must align the Three M's: raw materials (data), new machines (systems of intelligence), and business models.

Move AHEAD. Embrace the AHEAD model to demystify the application of the new machine in your business: Automate, Halo, Enhance, Abundance, and Discovery.

Last updated: April 13, 2025