AI Adoption in Business Reaches a Turning Point. What's Next? Companies are seeing increasing value in artificial intelligence, but now it's more vital than ever to invest in operation and infrastructure systems that can react and adapt to changes in a sustainable way.

By Roey Mechrez

Opinions expressed by Entrepreneur contributors are their own.

Achieving success in AI adoption was never going to be easy, but the past few years have brought significant progress, with McKinsey & Company reporting that many businesses are starting to see the value, including impact on revenues. Put simply, we may be entering a new phase on the artificial intelligence journey.

In 2020, there was actually "no increase in AI adoption," according to McKinsey's The State of AI (published in November of that year); rather, companies were "capturing value from AI at the enterprise level" in terms of revenue and cost reductions, with some even attributing 20% or more of their earnings before interest, taxes, depreciation, and amortization (EBITDA) to AI.

Following the Covid-19 outbreak, PwC has found that 52% of businesses accelerated their AI adoption plans, with 86% saying that it was becoming a "mainstream technology" in 2021. Many companies are now embarking on AI journeys, but there's a difference this time: they're not going into it blind. It's now a more familiar technology, and rather than being a "bright, shiny object," is becoming central to organizations.

The problem with AI adoption

The journey to achieving full value from AI will be longer and messier than in most technology transformations. The data, tech and talent involved will impact various functions across your organization, as well as those you partner with.

Its adoption is an ongoing process because AI function, as well as the data being fed into it, needs to be monitored throughout various phases of development, deployment and ongoing adjustments. Machine "learning" does exactly what it says on the tin: As data is added and changed, the AI learns from this information and it changes. Therefore, continuous adjustment and improvements are needed.

As businesses begin to understand and value AI, the key challenges so far have been around deployment, but we are beginning to see these resolved systematically. We now also have a few success cases and good examples for companies to learn and absorb best practices from, but it doesn't stop there.

Related: 5 Things Business Leaders Must Know About Adopting AI at Scale

Stages of adoption

Traditionally (if you can actually use that word in this context), an AI solution has three stages: planning, building or modelling and bringing to production. Now, it's time to focus on a fourth stage, and perhaps the most critical: operation. This is where assuming static data in the lab causes problems, because real-world AI solutions will have to deal with dynamic data, which can shift and change, so stability and robustness are vital for engineering teams to consider. The operation phase is also a key time for ensuring stability.

Stable and sustainable AI solutions require more than a model in production: In the operation phase, classic components should include monitoring abilities, observabilities, dashboards, feedback mechanics, data annotation and more. At more advanced stages, the operating team needs to think about retraining models and deploying them in the production environment, as well as advanced data screening, noise-handling and bi-directional feedback between the AI and the user.

The next phase

The operational stage will be critical over the coming two to five years. Those companies that have already planned, built and deployed successful AI models must now invest in maintenance and operation. Only with live feedback, dynamic data, continued testing and growth in the real-world environment can it continue to make an impact.

Related: What Fraudsters and 'Black Swans' Have in Common, How AI Can Mitigate the Effects of Both

Going forward, there will be an increasing need for the tools, products, methods — and crucially, people — to operate AI. This must be looked at across entire organizations so that teams can react to data changes in a scalable way. Looping in a whole data science team for a three-month project every time there's a shift in data is simply not sustainable; after all, the purpose of AI adoption is to automate processes and make life easier — not to use more manpower and cause more problems.

We're moving to a world where it shouldn't take 18 months to bring AI to production and operating it shouldn't be a hassle. The solution? Investing in operation and infrastructure and building an operation suite that can react to changes in a sustainable way.

Wavy Line
Roey Mechrez

CEO and Co-founder of BeyondMinds

Roey Mechrez is the CEO and co-founder of BeyondMinds. As a leading AI pioneer and global visionary, he is passionate about fostering a data-driven culture, using AI as a transformational catalyst to address complex regulatory, operational and business-intelligence challenges.

Editor's Pick

A Father Decided to Change When He Was in Prison on His Son's Birthday. Now His Nonprofit Helps Formerly Incarcerated Applicants Land 6-Figure Jobs.
A Teen Turned His Roblox Side Hustle Into a Multimillion-Dollar Company — Now He's Working With Karlie Kloss and Elton John
3 Mundane Tasks You Should Automate to Save Your Brain for the Big Stuff
The Next Time Someone Intimidates You, Here's What You Should Do
5 Ways to Manage Your Mental Health and Regulate Your Nervous System for Sustainable Success

Related Topics

Business News

Mark Zuckerberg Delivers Dorky Diss of Apple's Pricey New Headset

The CEO let his Meta team know what he thinks about Apple's Vision Pro, and he did not hold back.

Business News

Meta Unveils Twitter Competitor to Offer People a 'Sanely Run' Platform

The company is in talks with Oprah Winfrey and the Dalai Lama regarding commitments to the app.

Business Ideas

Top 25 Side Hustles to Make Money During Summer 2023

While the weather is warm, there are numerous ways to earn additional income. It is even possible to make money year-round with many of these ideas. But, here are the top 25 side hustles to make money during the summer.

Business News

After Being Told They Could Work From Home Forever, Employees Made Major Life Changes. Then, a New CEO Ordered Them Back to the Office.

Farmers Group CEO Raul Vargas is facing backlash for the change, but he says being in the office brings more "collaboration" and "innovation."

Business News

Hedge Fund Pays NYC Interns $20,000 a Month on Average, Sent to Lavish Palm Beach Kickoff

Citadel is known for its over-the-top parties and company retreats.

Growing a Business

How to Disrupt Hustle Culture and Build a Business That Supports Your Wellness

You can leave work at five each day. You can turn off your phone in the evenings and take weekends off. You can exercise. You can be fully present with your family. You will be better for it, and so will your business.