Why AI’s Biggest Value Is Not Speed but Redesigning Work

Two years ago the discussion about AI focused on whether it could answer basic questions; today AI is deeply embedded in office tools, meetings, data analysis, and daily business decisions, becoming a part of the workflow rather than just a chat assistant.

Level 1 – Faster execution of existing tasks. Simple uses such as drafting emails, preparing documents, or generating meeting summaries are now handled by tools like ChatGPT. While these applications improve efficiency, the author notes they are not the greatest value of AI because saving a few minutes on routine work is far from creating new productivity.

Level 2 – Accomplishing tasks that were previously impossible. The author’s company uses Microsoft Copilot, which is embedded in Word, Excel, and PowerPoint. A key example is complex spreadsheet handling: before AI, only finance specialists could manage advanced Excel functions, while other staff were limited to simple tables. With Copilot, users can describe their logic in natural language, and the AI automatically generates formulas and code, turning previously inaccessible tasks into routine operations.

Level 3 – Expanding cognitive boundaries. Using Excel again, the author discovered hidden features such as advanced visualizations, dashboards, and the ability to run Python code—capabilities that were unknown because of prior usage habits. AI surfaced these functions, prompting the author to study new Excel capabilities beyond formulas, illustrating how AI can reveal tools we didn’t know we had.

Level 4 – Reshaping the entire work process. In a sales scenario, the pre‑AI workflow involved an assistant sending regional performance tables, the salesperson manually filtering and analyzing them, and then deciding on actions. After AI integration, data is fetched automatically (e.g., via VS Code + GitHub Copilot), tables are generated, and AI writes an HTML report that includes analysis, key focus areas, and actionable recommendations. The salesperson now only needs to judge the AI‑provided suggestions, shifting from “doing the report and analysis” to “making decisions.” A similar shift occurs in Teams, where the AI assistant moves from merely taking minutes to actively offering viewpoints and suggestions during meetings.

The progression—from efficiency gains, to extending capability, to expanding cognition, and finally becoming a collaborative partner—demonstrates that AI’s greatest value is not making old work faster but prompting us to redesign how we work, a transformation that is already underway.