How to add artificial intelligence to your 2020 IT budget

As 2019 comes to a close, organizations are aligning goals and budgeting for projects for the new year. Here's how to make sure AI makes the cut.
Written by Macy Bayern, Multiplatform Reporter on

Artificial intelligence (AI) and machine learning technology are crucial to modern-day data-driven businesses, according to Gartner's recent AI and ML Development Strategies report. Nearly 60% of respondents said they have AI deployed in their businesses today, and expect to double the number of AI projects in place within the next year. 

Customer experience (40%) and task automation (20%) are the driving forces behind AI adoption, the report found. 

"AI can improve customer experience by understanding individual behaviors, preferences and/or purchase patterns, to perform predictive analysis," said Jim Hare, research vice president at Gartner. "This can drive better engagement by providing personalized recommendations and engagement at the right place, and the right time."

Task automation increases employee productivity by eliminating menial, repetitive tasks that take up valuable time, Hare said. By automating those tasks, employees have more time to conduct more meaningful, impactful work. 

Cost is another major factor behind AI adoption, said JP Gownder, vice president and principal analyst serving CIOs and CTOs at Forrester. "AI, if done correctly, can have a very positive return on investment," Gownder noted.

SEE: Tech budgets 2020: A CXO's guide (ZDNet/TechRepublic special feature) | Download the free PDF version (TechRepublic)

"A classic example would be that you are doing operational things in an old-fashioned way. You're sending field service technicians out to inspect lots and lots of machinery, let's say," Gownder said. "But if you use artificial intelligence, you can predict when those machines will fail, send the field service agent out before the machine fails rather than after the machine fails, and you can increase your uptime and make sure that operations are not interrupted."

Disadvantages of AI deployment

While most professionals recognize the numerous benefits of AI technology, the disadvantages are worth noting.

AI deployment won't be successful if it isn't set up for success by the organization. Lofty ambitions and excessive automation are two of the biggest mistakes companies can make, according to the Automation, AI, And Robotics Aren't Quick Wins report, written by Gownder. 

According to the report, automating too much too quickly, customers can easily be left in the dust, feeling alienated by an over-automated customer service experience. It also pointed out that high ambitions often result in money and time wasted, as AI deployment isn't a quick and easy road. 

However, failure is an inevitability along the way, and the advantages of successful AI deployment make the journey worthwhile. 

How to budget for AI 

Convincing stakeholders to budget for AI can be both intimidating and tricky. Both employees and stakeholders want the company to be successful; it's the job of employees to remind the stakeholders that AI could get them there. 

1. Create a tangible business case

"One of the problems that people do when they're trying to pitch these business cases is that they treat it as a before and after exercise. They say, 'I don't have a business case. Let me go in a room and put some numbers together,'" Gownder said. "This is not the best practice. You should be thinking about this as more of a business case life cycle, which is to say that the initial model you put together is just the beginning of what is really a process of diplomacy and alignment."

2. Collaborate with investors

Stakeholders and business leadership should all be involved in the business case for AI, Gownder said. Employees should be asking the people in power what they hope to get from AI. 

"You've got to become a diplomat," Gownder said. "'Say, 'Well, what would you be looking for within the parameters of this business case? How could we align our metrics? How could it help your customers?' You've moved into the vision and strategy phase, where you're co-creating that vision for what's happening."

"Hopefully you're then ready to collect some data in a pilot, which will cost a little bit of money in and of itself, but that'll help you to get data both on finance, but also your customers," he said. 

3. Use the business case as the pitch

Once all of the data is collected, the business case should be finalized and given to investors for consideration, Gownder said. 

This way of pitching is much different than traditional methods. Rather than pitching the idea, employees are instead putting in all the work first to create a knowledge-based argument for investment -- "this is much more effective than just sitting in a room and doing it," Gownder said.

Also See

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Research consortium builds new AI benchmark for understanding language

Apple, Microsoft, and Foxconn sign up to $108b SoftBank Vision Fund 2

China aims to overtake US as global leader in AI innovation (TechRepublic)

AI adoption: 40% of company leaders have 'no hesitation' (TechRepublic)

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