IDC and Forrester issued recently their predictions for artificial intelligence (AI) in 2020 and beyond. While external “market events” may make companies cautious about AI, says Forrester, “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.
Building on the proven success of these IPA use cases, IDC predicts that by 2022, 75% of enterprises will embed intelligent automation into technology and process development, using AI-based software to discover operational and experiential insights to guide innovation.
And by 2024, AI will be integral to every part of the business, resulting in 25% of the overall spend on AI solutions as “Outcomes-as-a-service” that drive innovation at scale and superior business value. AI will become the new UI by redefining user experiences where over 50% of user touches will be augmented by computer vision, speech, natural language and AR/VR. Over the next several years, we will see AI and the emerging user interfaces of computer vision, natural language processing, and gesture, embedded in every type of product and device.
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. By 2021, predicts IDC, 15% of customer experience applications will be continuously hyper personalized by combining a variety of data and newer reinforcement learning algorithms.
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.”
IDC predicts that by 2022, possibly as a result of a few high-profile PR disasters, over 70% of G2000 companies will have formal programs to monitor their ‘digital trustworthiness’ as digital trust becomes a critical corporate asset.
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.”
And IDC observes that “effective use of intelligent automation will require significant effort in data cleansing, integration, and management that IT will need to support. Resolving past data issues in legacy systems can be a substantial barrier to entry, particularly for larger enterprises.”
AI adoption is not consistent across all companies and we are seeing a new digital divide, a divide between the AI haves and the AI have-nots, those with or without the required highly-skilled engineers.
In 2020, says Forrester, the “tech elite” will ramp up AI plus design skills while other will “fumble.” Pairing human-centered design skills and AI development capabilities will be key. As for the rest of the workforce, by 2024, 75% of enterprises will invest in employee retraining and development, including third-party services, to address new skill needs and ways of working resulting from AI adoption, predicts IDC.
What constitutes “the workforce” will continue to expand and IDC predicts that the IT organization will manage and support a growing workforce of AI-enabled RPA bots as intelligent automation scales across the enterprise. Another addition to the workforce will an army of chatbots, assisting with a variety of tasks in the enterprise. But Forrester predicts that four in every five conversational AI interactions will continue to fail to pass the Turing Test. By the end of 2020, predicts Forrester, conversational AI will still power fewer than one in five successful customer service interactions.
Where the work is done will also continue to expand. As compute power moves from the datacenter to the edge, says IDC, IT will be challenged to manage and control edge processing devices. By 2023, nearly 20% of servers that process AI workloads using AI-optimized processors and co-processors will be deployed at the edge. And by 2025, 50% of computer vision and speech recognition models will run on the edge (including endpoints).
AI will be here, there, and everywhere, and IDC estimates that by 2025, at least 90% of new enterprise application releases will include embedded AI functionality. However, adds IDC, truly disruptive AI-led applications will represent only about 10% of this total.
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.”