Introducing work intelligence systems

Don’t underestimate complexity

If there is a moral here, it is not to underestimate the complexity of the problem and not to overestimate the ability of AI and data to provide you with critical insights. This is not to say that AI has no value; some insight and visibility are better than none. A bit of help to make decisions that guide your business is better than no help. Flip- ping the data scientist’s script to use AI effectively would be best. Rather than humans in the AI loop, it would help if you thought of AI in the human loop. Human knowledge, skills, and the context these provide should always be paramount in any business decision-making process.

The real world is too complex for AI to completely figure things out. By definition, AI will always have a limited view of what is happening across your business, and even this narrow view will not be 100% correct, but it still has value. The work intelligence systems that are starting to emerge aggregate and orchestrate data from various sources. They run powerful, AI-powered analyses across this data and provide previously unimaginable insights to support, augment, and inform your business decision making. These technologies ultimately aim to automate the decision-making process, but in our opinion, only the most basic, logical, and repeatable decisions should ever be automated.

In pragmatic terms, AI is indeed coming for senior white-collar jobs. AI vendors and unsuspecting buyers are driving that trend, and it will gain more momentum in the coming years. Work intelligence systems will gain traction in the enterprise, then backfire spectacularly if used too ambitiously. AI can and should be used to support senior white-collar work, not replace and automate those jobs. And, as glass-half-full analysts, we certainly hope that this is what happens, as it will bring a great deal of value and some amazing new insights.