AI Trends 2022: Spare Us the Hype, We Want Business Results

If you thought judgment, ethics, and even creativity were the unique purview of humans, think again.

The latest industry analyst predictions about artificial intelligence (AI) are out, and they’re certain to oust a ton of assumptions we’ve made to date. Read on to find out just how smart, creative, and sincere AI will become during the next few years.

Creative Machines Are the Future

Noting that South Africa granted the first patent to a creative AI system in 2021, Forrester researchers predicted creative AI systems will win dozens of patents in 2022. They were quick to point out that “AI will not own the products in the traditional sense – the developers of the AI systems…will still enjoy commercial benefits. But companies will experiment with creative AI, knowing that these innovations may be legally protected.”

Forrester Analyst Diego Lo Giudice looked ahead to “AI 2.0,” which he saw fueling the development of new creative business applications, exceeding basic expectations of AI to free up workers for greater creativity. He predicted that AI would connect business processes across silos to boost business creativity and wrote that “AI’s new business models can optimize the convergence of the digital world with the physical world and drive the ‘anything as a digital service’ trend. The impact on customer experience could be huge.”

Explainable AI Is Not Your Typical IT Project

Explainability and ethics were among the most widely discussed AI-related issues. Forrester Analyst Srividya Sridharan saw the market for responsible AI solutions doubling as industries adopt “responsible AI solutions that help companies turn AI principles such as fairness and transparency into consistent practices.” And for those who fear these algorithms will run amok, IDC analysts predicted that by 2025, to reduce reputational risks, 40% of G2000 companies will be forced to redesign their approaches to algorithmic decision-making, providing better human oversight and explainability.

AI explainability is one of topics that Ian Ryan is exploring as global head of the SAP Institute for Digital Government. It’s part of a research series for the Australian public sector on the value and impact of technologies for employees, citizens, and society at large. Ryan said that AI can help deliver citizen services with that coveted Amazon-like experience, provided organizations set value-based, measurable objectives.

“Applications of AI consist of the person using it, the AI model itself, and the information that comes from reality; these three pieces have to be in sync, targeted towards driving a particular outcome,” said Ryan. “You need to train the AI model continuously, keeping it updated so it can support workers as situations evolve, engineering out any bias while preserving data protection.”

For business value, AI algorithms cannot function as an inscrutable black box or operate autonomously. Ryan said organizations need to build explainability into complex AI models and involve targeted employees in AI model development.

“AI supports employees by taking tasks away, allowing people to be more productive and focus on high-value activities,” he said. “Al can access huge amounts of seemingly disconnected data from different places and identify patterns in seconds, far faster than humans. Explainability provides the transparency people can trust, so they’ll share their data knowing the organization will protect it and deliver value.”

Indeed, Gartner analysts warned that while AI will help companies emerge from the pandemic in a strong position, merely adopting AI won’t be enough. Companies need to operationalize updates to AI models, “using integrated data and model and development pipelines to deliver consistent business value from AI. It combines automated update pipelines with strong AI governance.”

AI Becomes Ubiquitous

Numerous analyst predictions tout the benefits of AI in strengthening human decisions. IDC researchers said that 85% of enterprises will combine human expertise with AI, machine learning, natural language processing, and pattern recognition to augment foresight across the organization, making workers 25% more productive and effective by 2026. IDC researchers saw 30% of organizations using forms of behavioral economics and AI- and machine learning-driven insights to nudge employees’ actions, leading to a 60% increase in desired outcomes by 2026.

More near term, Sridharan expected traditional businesses will take a page out of digital-native practices during the pandemic with an AI-first approach to platform and digital transformation. He said that “the more AI inside, the more enterprises can shrink the latency between insights, decisions, and results.”

Unlike many previous innovations, AI is not an isolated technology that organizations can surgically apply and wait for the magic to happen. AI is an extraordinarily powerful technology with profound ramifications for organizations and people as they discover its true business potential.

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