Is Artificial Intelligence getting real? | Straight Talk

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To find out, we look at some of the key predictions for 2019 and beyond

Artificial intelligence adoption, which has happened in fits and bursts till now, is all set to accelerate this year. That is if recent predictions of leading technology research firms like Gartner, IDC and Forrester for 2019 and beyond prove to be true.

Almost every technology research company seems to agree that AI is on the horizon, across industries and geographies. IDC, for one, has predicted huge investments in AI-driven user interfaces and AI algorithms at endpoint devices on cloud-enabled networks. Gartner has forecast exponential increase in AI-enhanced virtual healthcare and sophisticated AI-facial recognition technology and Forrester expects firms to lay the foundation to meet AI’s promise this year.

Analysts are not the only ones excited about AI. A huge number of CIOs seem to be on board too. AI emerged as the most mentioned and the top game-changer technology in the 2019 Gartner CIO survey that gathered data from more than 3,000 CIOs, representing $15 trillion in revenue and public-sector budgets and $284 billion in IT spending. “Four years ago, AI implementation was rare, only 10 percent of survey respondents reported that their enterprises had deployed AI or would do so shortly. For 2019, that number has leapt to 37 percent — a 270 percent increase in four years,” says Chris Howard, distinguished research vice president at Gartner.

Who will lead the way?

Results from Gartner’s survey align with IDC’s forecast that worldwide spending on AI systems will reach $35.8 billion in 2019, an increase of 44 percent over the amount spent in 2018. By 2022, it expects spending on AI to more than double to $79.2 billion.

"Significant worldwide artificial intelligence systems spend can now be seen within every industry as AI initiatives continue to optimize operations, transform the customer experience, and create new products and services", says Marianne Daquila, research manager, Customer Insights & Analytics at IDC, "This is evidenced by use cases, such as intelligent process automation, expert shopping advisors & product recommendations, and pharmaceutical research and discovery.”

According to IDC’s semiannual spending guide, Retail and Banking will lead in global AI spending. Retailers will spend $5.9 billion this year on tools like automated customer service agents and product recommendation generators, while the banking sector is expected to invest $5.6 billion on security, including automated threat intelligence and fraud prevention systems. As per IDC, discrete manufacturing, healthcare providers, and process manufacturing will be the next three biggest AI spenders.

If these ambitious plans pan out, new possibilities are bound to emerge. In its CIO’s Guide to AI, Gartner has identified several next-generation examples of use-cases in various industries.

  • Retail: Use an on-premises robot to bring requested items (such as different size, color) to a consumer waiting in a dressing room.  
  • Sales: Transcribe and analyze online sales meetings and calls and condense sales calls into actionable summaries.
  • Finance: Augment tax preparers’ expertise with AI techniques to optimize tax returns for each taxpayer. Algorithms process client answers to questions and a text analyst looks at legal and regulatory changes.
  • Security: Monitor video feeds to detect, prioritize and alert about potential or actual security incidents, based on intelligent image analysis.
  • Emergency services: First responders can identify victims more quickly, allowing for accelerated retrieval of medical information and first aid.

Try, Try Again

Clearly, opportunities are great, but so are challenges. According to McKinsey survey of over 2000 executives, the biggest barriers to AI adoption are lack of a clear strategy, followed by a lack of appropriate talent, functional silos that constrain end-to-end AI solutions, and a lack of leaders who demonstrate ownership of and commitment to AI.

Alexander Linden, research vice president at Gartner, seems to agree and says AI technologies can only deliver value if they are “part of the organization’s strategy” and are “used in the right way.” He says, “With AI technology making its way into the organization, it is crucial that business and IT leaders fully understand how AI can create value for their business and where its limitations lie.”

For the most digitized firms, McKinsey found lack of talent with appropriate skillsets was the biggest challenge. Executives responding to McKinsey survey are not the only ones worried about AI talent scarcity. Gartner warns that through 2020, 80 percent of AI projects will remain alchemy, run by wizards whose talents won’t scale widely in their organization through 2020. “The large majority of existing AI techniques talents are skilled at cooking a few ingredients, but very few are competent enough to master a few recipes — let alone invent new dishes,” says Daryl Plummer, Distinguished VP analyst at Gartner, “Through 2020, a large majority of AI projects will remain craftily prepared in artisan IT kitchens. The premises of a more systematic and effective production will come when organizations stop treating AI as an exotic cuisine and start focusing on business value first.”

That might not be easy for a technology as nascent as AI. “The next chapter in AI involves learning from AI pilots and proofs of concept and moving forward continuously and iteratively rather than throwing your hands up in defeat,” says Michele Goetz, Principal Analyst at Forrester. Her advice for CIOs taking this roller coaster ride: “Overcome your cautious cynicism by overplanning — dive in anyway and dabble. “You’ll make rookie mistakes. You’ll think of quitting. But you’ll strive on to reap tangible benefits and bragging rights.”