AI in the workplace

A study by Harvard University and Boston Consulting Group last year looked at AI in the workplace. Several hundred BCG consultants were given tasks of varying complexities and requirements, from screening resumes to creating ideas for new products and marketing strategies for them.

The group using AI (Chat GPT-4) produced 12% more output and completed tasks 25% more quickly than the control group. They also produced 40% higher quality output, with much higher improvements for below average performers.

Productivity Booster and Enabler

AI proved to be a productivity booster and quality disruptor. It acts as an enabler: People held back by language deficits or educational gaps are able to articulate better and faster. It also leads to better decision making: Knowledge workers can base decisions on unemotional analysis by an AI assistant who does not compete, and who does not just tell you what you want to hear.

Errors and Similarity

But the study also showed that using AI for complex issues, especially those that require empathy and human understanding, results in higher error rates. Another result was that, while using AI for creative tasks does speed up output, it also leads to similar results over time, whereas human ideation is more diverse. Humans are (still) better at creative problem solving and coming up with new ideas. 

Conclusions

It is clear that AI has the ability to help workers achieve better results faster and assist with a wide range of tasks. However, it is still difficult to set clear rules and determine benefits and challenges of the use of AI at work. So is dealing with inaccuracies that are delivered grammatically correct with seeming authority – and without any revealing body language. Blind faith in AI for everything is dangerous, just like ditching your GP and relying solely on Dr Google. 

AI results have to be questioned and we have to learn where to use AI as an assistant, as a creator and as an authority. And it is likely that the rules have to be adjusted continually, as capabilities grow.

For companies this means that ongoing training is critical, as is constant exchange of learnings and examples of wins and fails within trusted groups.