Why More Industries Will Implement Artificial Intelligence in 2017

Major industries including financial services, health care, telecommunications and education are using artificial intelligence to implement predictive analytics in applications that serve customers or leverage new business opportunities.

Current employees who do have deep industry knowledge often don’t have the analytical skills required to turn data into actionable insights. Last year, an MIT Sloan Management Review showed that 40 percent of companies report the lack of analytical skills as a critical challenge, but only 1 in 5 have done anything about it.

With AI being more widely used in the consumer and enterprise worlds, companies that do nothing will risk falling behind irretrievably. And, any outside analytical support will have to reshape its general data models to specific industry needs. Accenture’s partnership with Amazon Web Services is one recent example of an attempt to help clients marry industry expertise with robust data capabilities.

An AI system that swims in a data pool containing only credit-card transactions not only will become expert at detecting fraud, but also will be able to provide proactive suggestions. If your metadata shows you’re a frequent traveler, your bank not only will know not to deny you a coffee after your flight to Hong Kong, it also might prompt you to switch to a credit card that offers more frequent flier rewards points.

Technology vendors no longer will be able to make general appeals to the enterprise or try to woo consumers with aesthetics and style. The enterprise applications that succeed in 2017 must be able to map to specific customer and business paths, which varies widely by industry.

Data researcher IDG projects worldwide revenues for IT products and services will grow to $2.7 trillion in 2020, and a large proportion of that momentum will come from third-party platforms that aid companies in verticals such as financial services and manufacturing.

Selling a highly-integrated software application as a service means sales cycles are longer and product engineers must be involved right away, engaging directly with customer and prospects. Anyone whose sole job is to liaise between the two groups should be concerned about job security, even those with great “people skills.”

Big companies will eschew bloatware for applications that provide essential industry-centric applications and nothing else. Bloatware is defined as software whose usefulness is reduced because of the excessive disk space and memory it requires. IDC predicts worldwide spending on cloud applications will increase to more than $141 billion in 2019 from $70 billion in 2015, with the vast majority of growth in industry-specific applications.

Slack, the team collaboration software company, aggressively incorporated third-party apps to help its users build their channels into something much more than email. As Aaref Hilaly of Sequoia Partners said, services such as Slack that focus on integration and automation with existing systems will be used more often. Moreover, those services that people use daily can use AI to capture data automatically—something that big, isolated systems of record have yet to achieve.