- Companies are turning to consulting firms to help them figure out how to use AI effectively.
- Their customers are asking how machine learning and generative AI can transform their business.
- Consultants told BI they are also wondering how to make AI worth the investment.
You can ask the artificial intelligence almost any question.
But when it comes to how to use the technology, many companies are reaching out to consulting firms.
Providing AI advice is becoming an increasingly big part of many firms’ work: About 900 of PwC’s top 1,000 consulting clients are currently working with the firm to incorporate AI into their businesses, a spokesperson told Business Insider.
McKinsey & Company is set to make a record $16 billion in revenue in 2023, thanks in part to the generative AI boom. About 40% of the firm’s work is now AI-related, and a lot of that is now moving to GenAI, Ben Erenquigue, senior partner who leads global alliances, acquisitions and partnerships at McKinsey’s AI unit, QuantumBlack, told BI.
Meanwhile, Boston Consulting Group currently derives a fifth of its revenue from AI, with much of its work advising clients on GenAI, a spokesperson told BI.
“Eighteen months ago, the conversation was all, ‘What is GenAI?'” Alison Bailey, head of human resources and organization at BCG, told BI. “Now it’s, ‘How do we use AI to actually create value and drive meaningful change in how work gets done?'”
While some companies are focused on how AI can rewrite their strategies, others are asking consultants how to get started. The question might be as simple as where to best invest AI resources and training.
Bailey said the “people story” is crucial to this equation: Companies want to know how to mobilize their employees to take advantage of technology.
Greg Seward, strategy lead for technology, media and communications at KPMG US, said technology leaders at some companies are wondering whether they have the knowledge to make smart decisions.
“A lot of CIOs are worried they won’t have the right skills,” he told BI. They’re also worried about how to control technology and what the regulatory environment will be.
BI asked several consulting firms to share the most frequently asked questions about AI and the advice they found most effective. Here are some of the themes they identified:
Where to start
According to several consultants, many companies are still figuring out how to leverage AI and GenAI.
Jim Rowan, AI market activation leader and principal at Deloitte Consulting, told BI that companies new to AI should start by asking a few basic questions.
- What are you trying to achieve by deploying AI?
- Do you have the people, investments and systems to support implementation?
- Have you addressed data governance, privacy questions, potential bias, and other concerns?
If companies can answer these questions, they should outline areas where the technology can help, “and then closely measure and monitor its performance to make sure it is actually achieving its goals,” Rowan added.
According to Vlad Lukic, global leader of technology and digital advantage at BCG, companies also need to properly manage their own data, which is a key foundation for training GenAI. “The first step is to get your company in order from a data perspective, which will make things more seamless in the future, and that’s where the magic is,” Lukic told BI.
Roy Singh, global head of Bain & Company’s advanced analytics practice, told BI that people just getting started in AI should focus on short-term goals like understanding the technology and driving productivity gains.
Improving worker skills
Companies interested in AI know that technology is often only one part of the equation: the other part is keeping employees up to date.
Joe Atkinson, chief product and technology officer at PwC, told BI that it’s essential to help employees learn to use generative AI, rather than relying solely on hiring in-demand AI specialists.
Getting employees to use the tools may not be as hard as it seems: Atkinson said the technology is so accessible that just about anyone in a company could use it to develop products and services and make them more efficient.
Leading by example is important: Deloitte’s Rowan says senior executives should use AI to show how it can help, while also giving employees the time to explore the technology on their own.
“It’s important to raise expectations and communicate openly about AI adoption,” he said, so companies should host events like hackathons to encourage experimentation and educate employees about how AI can make them more efficient at work.
Reinvent your business
of Advances in AI will impact some companies more than others.
And in industries where AI is already forcing business models to be rewritten, companies need to think holistically about how they can leverage generative AI to reinvent their operations.
Bain’s Mr. Singh gave the example of the grocery industry, where companies like Instacart and Carrefour are using AI to “invent the next generation of customer experiences,” he said, adding that they’re not necessarily just looking to improve efficiency.
Most companies, regardless of how much work they’ve done with AI, should be flexible enough to adapt to new developments, according to PwC’s Atkinson.
He suggests that companies should build AI systems with an open architecture approach, a software design methodology that makes it easy to add, upgrade or replace elements.
Investment Return
Bain’s Singh said companies often wonder what productivity gains or other economic benefits they can expect from using AI.
But companies are starting to see tangible benefits and even big improvements from AI, he said. This could be true in areas like software engineering, finance and human resources.
Singh said many companies, especially those with lots of desk-bound knowledge workers, can expect to see a 15% to 20% productivity boost — and in some cases, much higher. Companies that can let AI take over repetitive tasks could see productivity increases of 50% or more, he said.
This doesn’t necessarily mean that each worker will get half their time back, but if the time it takes to complete a task is cut in half, someone in marketing, financial services compliance, or regulatory affairs in life sciences might end up getting a full day’s work back.
Singh said it may take two to three years for companies to achieve significant efficiency gains, but the opportunity is enormous.
In most cases, he said, it’s about setting expectations about how new AI is for many companies.
“We should all be humble and acknowledge that we are in the very early stages of the adoption cycle,” Singh said.
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