- Companies are turning to consulting firms to help figure out how to use AI effectively.
- Your customers are asking how machine learning and generative AI can transform their business.
- Consultants told BI that questions also include how to make AI worth the investment.
You can ask artificial intelligence almost any question.
But when it comes to how to use technology, many companies are directing their inquiries to consulting firms.
Providing AI consulting is making up a growing portion of many companies’ work. About 900 of PwC’s top 1,000 consulting clients are now working with the firm to incorporate AI into their businesses, a spokesperson told Business Insider.
In 2023, McKinsey & Company is expected to generate record revenue of $16 billion, in part due to the generative AI boom. Nearly 40% of the firm’s work is now AI-related. And much of that is now shifting to GenAI, Ben Ellencweig, a senior partner who leads alliances, acquisitions and partnerships globally for McKinsey’s AI arm QuantumBlack, told BI.
Boston Consulting Group, meanwhile, now generates a fifth of its revenue from AI, and much of that work involves advising clients on GenAI, a spokesperson told BI.
“18 months ago, the conversation was about ‘what is GenAI,’” Allison Bailey, head of people and organizational practices at BCG, told BI. “Today it’s: ‘How can I truly drive value with AI and drive meaningful change in the way we work?'”
Even as some companies focus on how AI can rewrite corporate playbooks, some companies are asking consultants how to get started. The question could be as simple as where it makes the most sense to invest AI resources and training.
Bailey said “people issues” are essential to the equation. Companies want to know how to mobilize their workers to embrace technology.
Greg Sward, head of strategy for technology, media and telecommunications at KPMG US, said some corporate technology leaders wonder whether they have the knowledge to make smart decisions.
“Many CIOs fear they don’t have the right skills,” he told BI. They are also concerned about how to maintain control of the technology and what the regulatory environment will be like.
BI asked several consultancies to share the most common questions they’re getting about AI and their best advice. Here are some of the themes they identified.
Where to start
Many companies are still determining how they might use AI and GenAI, according to several consultants.
Jim Rowan, AI market enablement leader and principal at Deloitte Consulting, told BI that companies that are new to AI should start by asking a few basic questions:
- What are we trying to achieve by adopting AI?
- Do we have the talent, investment and systems to support implementation?
- Have we addressed data governance, privacy issues, potential bias and other concerns?
If a company can answer these questions, it should outline areas where the technology will be useful. Then, “closely measure and monitor your performance to make sure you’re actually achieving your goals,” Rowan added.
According to Vlad Lukic, global leader of BCG’s technology and digital advantage practice, companies must also have good control over their data. This is the crucial foundation for GenAI training. “The first step is to make sure you have your house in order from a data perspective. This allows for greater fluidity in the future and that’s where the magic lies,” he told BI.
Roy Singh, global head of Bain & Company’s advanced analytics practice, told BI that those starting to use AI should focus on short-term goals, such as understanding the technology or generating productivity gains.
Developing workers’ skills
Companies interested in AI know that technology is often only part of the equation. Another component is ensuring that workers are up to speed.
Joe Atkinson, PwC’s chief product and technology officer, told BI that it’s essential to help employees learn how to use generative AI, rather than relying solely on recruiting AI experts, who are in high demand.
Getting workers to use the tools may not be as difficult as it seems. Atkinson said the technology is so accessible that almost anyone in a company could use it to create products or services or to be more efficient.
Leading by example is important. Senior managers should use AI to demonstrate how it can be useful, while employees should be given time to explore the technology themselves, according to Deloitte’s Rowan.
“It’s important to create enthusiasm for AI adoption and communicate openly,” he said. Therefore, companies should organize events like hackathons, encourage experimentation, and educate workers on how AI can make them more efficient in their work.
Reinventing your business
O Advances in AI will affect some companies more than others.
And in industries where AI is already forcing a rethinking of business models, companies need to think comprehensively about how they can reshape operations with generative AI.
Bain’s Singh pointed to the grocery business. Companies like Instacart and Carrefour are looking to “invent the next-generation customer experience” using AI, he said, adding that they aren’t necessarily just looking for efficiency gains.
Most companies, regardless of how much they have become involved in AI, should be flexible enough to accommodate new developments, according to PwC’s Atkinson.
He suggests that companies should build AI systems with an open architecture approach, which is a way of designing software that makes it easy to add, update or swap elements.
A return on investment
Bain’s Singh said companies often wonder what kind of productivity gains and other financial benefits they can expect from using AI.
However, he said companies are starting to see measurable gains — sometimes even big improvements — from AI. That could be in areas like software engineering, finance or human resources.
Singh said many companies — especially those loaded with knowledge workers doing office work — can expect to see productivity improvements of 15% to 20%. Sometimes it’s much bigger. In companies where AI can take over repetitive tasks, productivity increases can be more than 50%, he said.
This doesn’t mean that every worker necessarily gets half their time back. But if the time it takes to complete some work is cut in half, then someone working in marketing, financial services compliance or a life sciences regulatory role could eventually get back the equivalent of a full day’s work.
Singh said it could take a company two to three years to make major efficiency gains, but the opportunity is immense.
In most cases, he said, it’s important to set expectations about how new AI is to many companies.
“We should all have the humility to admit that we are very early in the adoption cycle,” Singh said.
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