Personal Productivity AI Versus Enterprise AI

In the first stages of any major technology breakthrough, there is often a three-blind-men-describing-an-elephant effect at work. In the case of artificial intelligence (AI), its vast potential has people looking at it from their single perspective to the exclusion of others. It’s that narrow focus that has lent itself to the “Saaspocalypse” meme earlier this year. AI is already having a profoundly positive impact on the performance and efficiency of personal productivity applications, including spreadsheets, documents and presentations. While this will improve the productivity of individuals and small workgroups, it’s probable that organizations will misuse these tools, applying them to what should be left to software designed for enterprise use. ISG Research asserts that through 2029, midsize to very large organizations will misuse AI-enabled personal productivity tools for enterprise-wide tasks, creating serious security, control and governance issues.

As is the case today for business software users, the personal productivity domain is distinct from the enterprise domain, but there are many cases where the former extends into the latter. Spreadsheets are the best example: For decades, almost everyone acknowledged the defects of stand-alone spreadsheets used in enterprise processes, but used them anyway. The failures and losses caused by the misuse of these tools go largely unnoticed and unacknowledged. There is also the opportunity cost measured in time wasted trying to make personal productivity software do what it was never designed to do.

There is significant scope for AI to substantially extend the functionality of personal productivity applications in ways that are already here and will grow more powerful and affordable in a relatively short period of time. Some of the most common that are most applicable to spreadsheets include:

• Natural language processing, which enables users to describe what they are trying to accomplish and the application automatically and (if necessary) interactively orchestrates the routines, data, macros, formulas and so on.
• Predictive analytics and trend forecasting, which bring more nuanced and sophisticated approaches to common business tasks, such as forecasting, planning and budgeting.
• Automated data cleansing, which scans data sets to remove duplicates, standardizes formatting and highlights anomalies to eliminate errors.
• Automated visualization and reporting, which suggests and builds the ideal charts pivot tables, visual dashboards and tables based on spoken or text prompts.
  
  

Each of these can make even casual users of the software far more competent and capable of completing tasks with limited training in a fraction of the time it would normally take them, even if they were power users. Capabilities once available to IT professionals or in enterprise software will increasingly be within reach of power users and, even to a limited extent, casual ones.

The same expansion of the competence frontier and corresponding shrinking of time to complete tasks applies to every category of personal productivity software. This is most obvious in enabling people to write faster and more effectively, but it has applicability for streamlining the creation of business presentations that conform strictly to existing company formats and norms. For those so inclined, the creation of small application agents and related programming tasks is far more approachable with existing AI technology and is likely to become even more so and more affordable within this decade.

But it's also clear that the same challenges posed by legacy personal productivity applications will remain—and be potentially more consequential—when they are supercharged by artificial intelligence. When used for a wide range of appropriate tasks, increasingly AI-enabled personal productivity tools will multiply individuals’ competence and extend the scope of work they can be expected to perform. The same applies to small workgroups (fewer than 10). But these tools cannot reliably handle enterprise-wide tasks and workflows, for the same reasons as before—but especially not security, governance and controls.

AI-enabled personal productivity software and AI-assisted programming will be a boon to individual and small-group productivity. But these will not fundamentally alter the business software or competitive landscape of the enterprise software industry. The rationale for the division will remain. I strongly recommend that IT organizations focus on creating and managing policies and guardrails to prevent the misuse of personal productivity tools for enterprise tasks, while ensuring that individuals and small workgroups are not prevented from using expanded capabilities to the fullest.

Regards,

Robert Kugel