Continuing on the theme of SaaS Apocalypse due to AI, let’s talk about what AI will truly do for workers and why is AI succeeding? A recent survey shows most American workers are dissatisfied with their job. Pay tops the list, but growth and development are also high on the list. AI excels by performing similar but different tasks, repetitively while for humans that job becomes tedious.
Snaplogic’s survey showed that 90% of workers are burdened with boring and repetitive tasks. Now employees are able to use AI to deal with much, but not all of their daily work flow. For technical people that operated in MS Office, they may have recorded a macro, but fell short of optimizing for different scenarios. Now a simple dialog with Claude, Gemini, or ChatGPT can result in a basic version of the macro and with further prodding, and no coding knowledge make adjustment to handle a wider variety of instances seen in the workflow.
What does this mean for the future? Companies can expect 100s if not more “AI bots” that are there to help workers. United Health claimed to have over 1000 use cases for AI. However, each workflow will be different as the interpretation is based on the user whereas today’s SaaS solutions are common across all users. The results become user specific.
Problems for companies in the AI future:
- How to standardize AI output for consistency
- Pareto principle: AI will handle 80%. Can the remainder be structured to fit within AI use cases
- How much of an external SaaS solution can be rebuilt that can justify time and cost savings
- Use AI on internal data to make AI smarter daily
The AI race at companies will lead to companies moving from standard solutions that employees customize to customized employee solutions. The key question for employees is how big the mess will get before solutions get standardized.
Having worked at large companies where everyone desired their own workflow, and justified their need for customization, the current era of self-sourced employee solutions will result in a defined solution set to minimize operation risks.