Less than two-fifths of companies have an AI strategy even though three-fifths believe current competitors will begin using AI, according to a new MIT Sloan Management Group survey. Approximately 85% of executives think AI will ensure a competitive advantage for their company, and three-quarters think it will allow them to move into new businesses.
Approximately 16% of respondents believe their company understands AI development costs while 17% do not; 19% say they understand the data such development requires while 16% do not. These disparities, along with differences in big-picture understanding of what AI holds for business potential, workplace implications and industry context, has led to uneven implementation of the tech across industries.
The study divided companies and organizations into four maturity clusters based on understanding and adoption of AI: pioneers, investigators, experimenters and passives. The composition of each group among the surveyed population is 19%, 32%, 13% and 36%, respectively. Pioneers — those leading and innovating in AI tech — were more likely to develop their systems internally whereas organizations with less implementation and understanding were more likely to outsource.
Artificial intelligence applications are sweeping across industries, from airlines to hospitality to ride-sharing and food delivery. But this technology, which seems to be taking over so many core digital platforms, may currently have an inflated reputation of prevalence.
The study found there exists few cultural barriers to AI services and products across all maturity categories. The tech industry has certainly seen no shortage of successful AI applications and losing jobs to automation is not expected to significantly displace workers, so the shortage in AI strategies and systems today is significantly explained by a lack of knowledge.
The burden of this shortfall falls on executives who set company strategy. CIOs and other high level personnel need to understand AI’s implications in their field and for their company, especially if obvious applications are harder to find.
Paths to finding AI applications are plenty. Individuals can become an AI expert on their own through Andrew Ng’s online deep learning course, and companies without infrastructure or specialists can outsource to third party vendors.
A push for democratized AI systems is opening up opportunities for companies to easily use AI for the first time. For example, "drag and drop" AI algorithms open up AI and machine learning services for employees without technical coding knowledge.
The key for AI experimenters and passives is finding these applications now and putting them in place before their competitors beat them to the bunch and pioneers and investigators pull so far ahead they can no longer catch up