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Forrester: 3 high-profile PR disasters will “rattle” reputations; top AI predictions for 2020

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Forrester issued recently predictions for artificial intelligence (AI) in 2020 and beyond.

According to the report, while external “market events” may make companies cautious about AI “courageous ones” will continue to invest and expand the initial “timid” steps they took in 2019.

According to Forrester’s various surveys,

  • 53% of global data and analytics decision makers say they have implemented, are in the process of implementing, or are expanding or upgrading their implementation of some form of artificial intelligence.
  • 29% of global developers (manager level or higher) have worked on AI/machine learning (ML) software in the past year.
  • 54% of global mobility decision makers whose firms are implementing edge computing say that the flexibility to handle present and future AI demands is one of the biggest benefits they anticipate with edge computing.
  • 16% of global B2C marketing decision makers planned to increase spending on data and analytics technologies, including AI, by 10% or more this year.

In 2020, Forrester predicts that

25% of the Fortune 500 will add AI building blocks (e.g. text analytics and machine learning) to their Robotic Process Automation (RPA) efforts to create hundreds of new Intelligent process automation (IPA) use cases. “RPA needs intelligence and AI needs automation to scale,” says Forrester.

As a quarter of Fortune 500 enterprises redirects AI investments to more mundane shorter-term or tactical IPA projects with “crystal-clear efficiency gains,” around half of the AI platform providers, global systems integrators, and managed service providers will emphasize IPA in their portfolios.

Emerging technologies are high-risk technologies. In 2020, warns Forrester, 3 high-profile PR disasters will “rattle reputations,” as the potential areas for AI malfunction and harm will multiply: The spread of deepfakes, incorrect use of facial recognition, and over-personalization.

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Accentuating the positive, Forrester is nevertheless confident that “these imbroglios won’t slow AI adoption plans next year. Instead, they will highlight the importance of designing, testing, and deploying responsible AI systems — with sound AI governance that considers bias, fairness, transparency, explainability, and accountability.”

Leadership matters, says Forrester, and companies with chief data officers (CDOs) are already about 1.5 times more likely to use AI, ML, and/or deep learning for their insights initiatives than those without CDOs.

In 2020, senior executives like chief data and analytics officers (CDAOs) and CIOs who are serious about AI will see to it that data science teams have what they need in terms of data.

The real problem, says Forrester, is “sourcing data from a complex portfolio of applications and convincing various data gatekeepers to say yes.”

So we have to wait another 5 years to see the “truly disruptive” potential of AI finally realized and only in a few cases? Another Forrester predictions report indeed warns that in 2020, “the exuberance in AI will crescendo as expectations come back to earth.” While Forrester predicts another new peak in AI funding in 2020, it asserts it will be the last one—“with more than 2,600 companies globally, the AI startup ecosystem is a saturated market.”

The most significant signal of the coming slowdown, according to Forrester, is the fact that 20 AI companies have raised unicorn-sized funding rounds in the past 12 months. “This cannot be sustainable,” says Forrester.  Which reminds me of Charles Mackay’s Extraordinary Popular Delusions and the Madness of Crowds: “The bubble was then full-blown and began to quiver and shake preparatory to its bursting.”

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