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5 Enterprise AI and Automation Predictions for 2023

November 22 2022

4 min read

cityscape at night

“AI” and “Automation” are still the hottest buzzwords in the enterprise space, and they’re showing no sign of slowing down.

So what does 2023 hold for companies and their increasing investment in artificial intelligence, automation, modernization, and transformation?

Here are my top five predictions for the year ahead.

1. Onshoring Drives Labor Productivity Increases

The early part of this century brought with it rapid globalization: Supply chains crossed borders; trade agreements surged; exports and import volumes rose; many countries invested aggressively in other regions, and companies outsourced labor to take advantage of lower costs.

But as China and the U.S. dialed up innovation rates for the AI Arms Race, each country looked to protect its intellectual property and bring as much hardware and software development back home.

This will lead to more pressure on CEOs and leadership teams to bring as much back onshore as possible in 2023—data, IP development, supply chains and critical workforce members will all be part of this call home.

2. The Reign of the Augmented Employee

2023 will mark the end of the widespread thinking that “robots will replace humans at work” and shift towards “robots will augment humans at work.”

An article in The New York Times by Farhad Manjoo, “In the Battle With Robots, Human Workers Are Winning,” started talking about this change in sentiment this month. Manjoo argued that machines and software would aid human work, not replace it, best summed up with this line: “Radiologists who use A.I. will replace radiologists who don’t.” Human and machine collaboration is the way forward and is the best way to increase labor productivity and outcomes.

One job area that I envision will grow in prominence is the MLOps (Machine Learning Operations) teams, where jobs to do basic data entry might fall by the wayside. We may see entire teams and departments emerge to design, build, and optimize ML models.

The Reign of the Augmented Employee

3. The Year of Return-On-Investment

2023 will mark the year of investments that pay off both in the short and long term. To date, it’s been hard to benefit from both. Until recently, any promise of long-term payoff has meant 2-5 years of time-intensive and sometimes painful efforts to work with a system integrator and re-engineer processes.

In the context of a recession and modern software prioritizing time to value and near-term ROI, the technology driving AI and intelligent automation forward must have short-term benefits and also be future-proof with long-term payoff.

McKinsey’s 2021 The State of AI Survey found that one-third of companies saw more than a 5% increase in revenue driven by AI technologies and that around 10% of customers saw more than a 10% decrease in costs caused by AI technologies.

4. The Year of Narrow Applications

I hear this a lot: “AI has turned a corner.” It has turned many corners. But while AI has developed remarkable skills, they are specific and non transferable.

As smart as algorithms are getting, they are still very narrow in what they can solve. General human intelligence allows us to take learnings from one area and apply them in entirely different settings—we do not start from scratch whenever we want to learn something new.

While these are all phenomenal steps forward, they are all single-use case achievements. Computers cannot use learnings from one use case and apply them to another—that would imply some degree of general-level intelligence of AGI. 2023 will be the year of applying ML models and automation software to specific, focused use cases.

5. The Arrival of Regulation

Not much has been done in the way of AI regulation, and there has been little talk of its ethical use. In 2023, that will change. It’s being increasingly surfaced by Hyperscience’s customer base—a core reason why we established an AI ethics committee earlier this year.

Over the next year, several areas of debate will spark surrounding (A) bias in data and (B) the push for AI to promote social good and prevent social harm.

For example, six major robotics companies recently signed an open letter pledging never to allow or pursue the weaponization of their general purpose robots. The non-binding letter was signed by Agility Robotics, ANYbotics, Boston Dynamics, Clearpath Robotics, Open Robotics, and Unitree Robotics.

Regulation will likely come at a country-by-country level, with the two major AI powerhouses (US and China) taking very different approaches.

For a more detailed look at my predictions for 2023, read the full ebook here.

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Automation predictions for 2023