Now that various forms of artificial intelligence are getting a workout in real-life markets, data is emerging highlighting some of the ups and downs.
Early adopters of AI report strong opportunities, according to one view, while another study points to the need for changes in current processes.
The majority (76%) of executives in ‘cognitive aware’ companies expect AI to transform their organization while most (69%) anticipate minimal or no job losses.
The study, comprising a survey of 250 U.S. executives conducted by Deloitte, found that almost a third (29%) of businesses see the addition of new jobs being created along with the adoption of AI.
However, there are some potential pitfalls ahead, at least for some departments, as I wrote about here last week (The Bumpy Road Ahead For AI In Sales, Customer Service).
The reality is that deploying artificial intelligence is hardly a simple undertaking.
The majority (55%) of businesses deploying AI have not received any tangible business outcomes and 43% say it is too soon to tell, based on a new study by Forrester.
That study, comprising a survey of 3,400 executives in 10 countries, found that the majority (51%) of companies are investing in AI, an increase from 40% a year ago.
The study suggests that unless firms plan, deploy and govern it correctly, new AI tech will provide only meager benefits or even unexpected and undesired results.
One reason to get AI right: 73% of execs say that being highly responsive to rising customer expectations is one of their top priorities over the next year. Artificial intelligence, done right, can help them do that.
The study that really needs to be done is whether companies exploring and (esp.) using AI "leaped" into AI without any inter-mediate steps having to do with big data, BI, predictive modeling and forecasting, etc. Or whether it can successfully be learned and deployed without "standard analytics" chops.
I have slightly different view why AI is not working well. To begin with all of marketing on the net has greatly changed. 4 to 5 years ago, Google Hummingbird algorithm was installed. This change started a number of additional changes how products are sold on the net and more importantly how they are advertised and marketed.
These modeling changes continue to this day not only by Google Search but also to the reactions from the advertisers to those changes.
There are too many moving parts, changes and adjustments in the market place for AI to be affective. There is a future in AI but I think it needs to start slower with better and more stable data points.
Totally correct, Patrick.
Good points, Craig. In some cases, that is happening. Starting slower and realistically really are key.
This is relatively new, not mainstream technology. As withh all other lines of tech, it will take time, with trial and error, before there are tangible results.
Good point, Henry. Though AI in various forms has been around for many years, it's just starting to take off in a big way for a host of reasons.