The End of the Information Economy (As We Know It)

For most of the last fifty years, knowledge work has run on a simple bargain: you were paid for your time. Hours at a desk, processing and communicating information, were the unit of value. That bargain is ending. AI is automating the work itself, and the economy is quietly shifting from paying people for the time they put in to paying for the outcomes they produce. This is the heart of The Value Shift — and the information economy is where it lands first.

We are in the middle of a new industrial revolution for knowledge work. The implications reach well beyond technology teams, reshaping productivity models, workforce structures, and economic demand across industries. And it is unfolding far faster than almost anyone expected.

The shift is happening now, not someday

This is not a forecast. Current technical capabilities indicate that the majority of information tasks can already be automated. Intelligent automation is poised to increase overall information-worker productivity in the range of 8–10× by 2028. The window in which leaders get to decide how they respond is measured in months, not years.

• 80% of information work is now automatable.
• 18–24 months is the expected timeline for large-scale disruption.
• 8–10× productivity increase is projected by 2028.
• 2 people will accomplish what takes roughly 20 today.

The choices made in the next 18 to 24 months — whether to scale, restructure, or reinvest — will determine who stays competitive in an AI-driven economy.

Why the estimates keep getting revised up

A September 2025 report from McKinsey put it at “45% of information work is automatable with the technology available today,” translating to a projected impact on 12 million jobs by 2030. But Microsoft’s announcements at Ignite suggest those numbers significantly understate both the scale and the speed of change underway. New tools and capabilities indicate that as much as 80% of the tasks information workers perform today can be automated with existing technology, and that the timeline for widespread automation is collapsing into the next 18 to 24 months.

Individually, the Ignite announcements look incremental. Taken together, they radically change what an information worker’s role even is:

• A unified Copilot across Office, with agent mode. Copilot now spans Word, Excel, PowerPoint, Teams, and Outlook, and a new agent mode lets it execute actions inside those apps — completing entire workflows in less than 10% of the time manual work would require.
• Computer Use by Agents (CUA). Autonomous agents can connect to a cloud-based virtual machine and operate Windows and web interfaces by analyzing the screen. The implication is stark: if a person can be trained to do a task, it can now be automated — no connectors or APIs required.
• Copilot Studio and Agent Flows. Microsoft merged RPA capabilities with AI-driven reasoning in a single platform, so information tasks can be automated, packaged as agents, and triggered by others or run autonomously.
• Agent Builder. Embedded in M365 Copilot, it lets business and information users build simple agents that automate their own tasks.
• Agent identities. Agents are assigned identities through Entra — email addresses, permissions, and SSO access to third-party applications, like any other member of the team.

What this does to the workforce, 2025–2028

Over the next two years, the IT and information workforce will change dramatically as companies adopt deep automation to drive productivity. By 2028, aggregate productivity among information workers is expected to rise eight to ten times. Tasks that take twenty people today will be handled by two.

The honest disagreement is about magnitude. The public fears something in the 10–20% range. Management, following McKinsey, expects 40–50%. The technologists and robotics experts closest to the tools predict up to 80%. Jobs once considered stable — human resources, finance, IT helpdesk, customer service — are now at risk and could become obsolete within three to five years. The roughly 20% of roles that evolve rather than disappear will become heavily augmented by automation rather than eliminated.

The information economy — where organizations and individuals created value primarily by acquiring, processing, and communicating information — is undergoing a fundamental restructuring. As AI makes 80% of information tasks automatable, the economic basis of information work changes. This is not a prediction. It is a description of what is happening now.

Two ways to prepare — and three ways to harvest the gains

To navigate the shift, companies have to adapt deliberately. Two principal strategies stand out:

• Process-based transformation (top-down). Identify the key business functions and processes that can be re-engineered and automated with AI and modern tools. This is the path enterprise architects, consultants, and IT leaders recommend. It carries real risk — it is costly, and failure burns time and money — but the upside is the largest.
• Individual productivity-based transformation (bottom-up). Ask every employee to find at least one task they can automate to save roughly four hours a week. The cumulative effect is about a 10% increase in capacity, with low investment, low risk, and no workforce disruption.

Productivity, once unlocked, has to go somewhere. There are three ways to harvest it:

• Scale up. The same workforce achieves eight to ten times the results.
• Get lean. The organization maintains current results with roughly 20% of the workforce.
• Reinvest in growth. Productivity gains let the company streamline cost centers and pour the savings into profit centers.

None of these is automatically right. Choosing among them is exactly the kind of decision The Value Shift argues leaders should make early and on their own terms — while they still control the timing — rather than having the decision made for them under pressure.

Guidance for the people doing the work

For IT staff: the first question is whether you are genuinely an IT professional or an information worker who happens to sit in the IT department. Developers, designers, engineers, and certain architects will lead this transformation. The highest-leverage move is to focus on the data — cleaning up complex data foundations, identifying what exists, knowing where it lives, and integrating it so automation has something solid to stand on.

For information workers: those who choose to ride the wave have to act quickly. Learning to build and operate AI agents that automate tasks is the skill that matters. For anyone who declines to upskill, organizational initiatives — or unemployment — may force the issue anyway. Anticipating that early is how you keep control of the timing and the options for your next move.

The same logic, scaled up to the whole economy

Strip it back and the pattern is the one running through The Value Shift. When the work can be automated, time stops being the thing anyone pays for. Value moves to outcomes — to the judgment about what to automate, what to keep human, and what to do with the capacity that gets freed. The information economy isn’t disappearing so much as being repriced, and the organizations that thrive will be the ones that decide deliberately, early, and on their own terms.

The right first move isn’t to automate everything. It’s to get clear-eyed about what can be automated in your environment — not in the abstract, but in your actual processes — and then choose, on purpose, whether to scale, get lean, or reinvest.