
Please do not leave this page until complete. This can take a few moments.
When Bret Greenstein was in the sixth grade, his teacher demonstrated how a computer could learn and then recite someone’s name.
That’s when Greenstein said he became intrigued by artificial intelligence. Since then, he’s been on a more than 30-year career journey focused on IT and emerging technologies, including stints at IBM and Cognizant.
Today, Greenstein, a Danbury resident, is part of the senior leadership team in charge of artificial intelligence at one of the world’s largest professional services and consulting firms, PwC.
The company, which has several Connecticut offices, is bullish on AI, and has made a big bet on the technology.
In April, PwC announced it will invest $1 billion in generative AI over the next three years to automate parts of its tax, audit and consulting services. It will also use its learnings to help clients with their AI adoption.
PwC is working with Microsoft Corp. and ChatGPT-maker OpenAI on its AI transformation, said Greenstein, a data and analytics partner.
“We’re changing everything, finance, HR, how we do delivery, how we do M&A, using generative AI to handle all of our confidential data, and to do it in a way that drives productivity and scale,” Greenstein said in a recent interview.
Greenstein said companies of any size can begin to experiment with generative AI, a type of artificial intelligence that uses algorithms to create new content like text, images, sound and other media.
The tech phrase became part of the American lexicon nearly a year ago with OpenAI’s launch of ChatGPT, an artificial intelligence text chatbot.
Most companies will use the technology to automate various business processes, such as customer service and data analysis, with the goal of scaling their workforce, saving money and quickening the pace of certain tasks, Greenstein said.
For example, PwC recently launched an internal generative-AI tool — called ChatPwC — that provides employees feedback on common questions related to taxes and regulations.
In another example of AI’s potential use, Greenstein said he was recently consulting for a client that makes home-improvement products and gets constant calls from customers and contractors asking for help on product assembly and installation.
The company wants to create a generative AI-backed self-service program that incorporates its product instructions and other how-to documents to speed up the time it takes to answer consumer questions.
“That’s a very cool use case and very doable with today’s technology,” Greenstein said.
AI will have key uses in major industries in Connecticut, he added, including health care, banking, utilities and insurance.
It can, for example, be used to transform insurance call centers by extracting and then using customer information to create a claim.
And AI isn’t reserved just for large, deep-pocketed corporations, Greenstein said.
Smaller companies can and should consider experimenting with the technology, possibly using off-the-shelf generative AI models, like ChatGPT, to improve processes.
For example, Greenstein said he knows a company with 100 electricians using generative AI to help manage service requests and records.
A small public relations firm could use the technology to write client press releases.
“I think what AI will do is allow small companies to act like larger companies because it will allow them to scale their workforce,” he said. “And I think large companies are trying to figure out how they can take out a lot of costs and act with greater speed, so they can act like a nimbler, smaller company.”
According to a recent PwC study, AI will have a transformative economic impact, contributing up to $15.7 trillion to the global economy by 2030. That’s more than the current output of China and India combined.
Of that amount, $6.6 trillion is likely to come from increased productivity, and $9.1 trillion from consumption-side effects, according to the study.
AI’s economic impact will be driven by productivity gains from businesses automating processes and augmenting their existing labor force. It will also create increased consumer demand from the availability of personalized and/or higher-quality products and services, according to PwC.
Greenstein recently chatted with HBJ about AI’s current and future impact on businesses.
Here’s what else he had to say. The Q&A was edited for length and clarity.
What stage of AI development are we in right now?
A. So, in AI broadly, it’s like springtime. Flowers are blooming. But in generative AI, it’s still very early. Maybe it’s the first week of spring.
The point is, each of the models and capabilities continue to leapfrog each other. You’re going to see this massive amount of innovation in the next two years, where the models themselves become more capable at a wider set of things.
That means performance will improve, the number of things that it can do will grow, and the cost of using it will go down.
How widespread is AI adoption among businesses?
A. For the enterprise or corporate market that we serve, you’ve got the bulk of businesses that are in early stage exploration.
Companies are making what I call safe bets at the moment, doing things where they can drive real outcomes and gain incremental business value. In the future, I think you’re going to see business models built around AI more.
Right now, a company may be experimenting with AI on how they handle invoices, but wouldn’t it be more interesting to change your entire supply chain?
However, it would be very risky at this point to make those types of drastic changes, until the underlying technologies are really maturing and not evolving so rapidly.
There are a few real leaders today who are doing what I’ll call disruption. In almost every sector, they’re trying to find the disruptive business model where AI makes something happen that is simply impossible today.
I see it in payroll and mortgage processing, insurance, health care — they’re all trying to find this new way, where you could ten X the work productivity with AI and drive something different.
All companies have access to AI technologies, but the companies that invest in it to drive differentiation are the ones that are going to have an advantage.
Which industries do you think AI will impact the most?
A. It’s clearly applying to places where you’re seeing pools of labor doing lots of things. So, in industries where you have customer service, where you have huge volumes of inbound communication, like tons of customer requests, invoices, contracts, things like that, that’s where AI is ripe for implementation.
The use of AI doesn’t really apply to a single industry, it’s more about the pattern of work. You’re going to see more likely adoption with organizations that have high volumes of document-based work.
You see that in the legal and education industries as well as banking, insurance and health care — they have got paper flowing everywhere.
Companies are using generative AI to answer customer purchase emails, for lease abstraction (or extracting, processing, and organizing critical lease data) and also to help handle mortgage applications.
I think if you look at everything from utilities, to insurance companies, to banking, it’s going to certainly drive improvements, especially in customer service.
I think it’s also going to help with the ability to understand what customers feel and want. One of the examples that came up recently was in customer service. When you do an interaction with customer service, at the end of a call, they always ask if you’d be willing to stay on for five extra minutes to do a survey.
Well, if you’re unhappy, the answer is always no. And even if you’re happy, the answer is no because we’re busy. Instead, what if you use generative AI to listen to the entire dialogue to develop an assumption of how a customer felt based on the tone and intensity of the discussion.
I think AI is going to allow us to better adapt to customer input.
What impact will AI have on the labor force?
A. What most people are saying is it’s going to drive a whole new class of jobs. The jobs that people have are going to focus more on critical thinking, judgment and higher levels of work because a lot of easier knowledge work will get done using AI.
But it also creates all kinds of new opportunities and roles, whether it’s managing the data, or making AI systems work well, or integrating AI into business or new business models.
If the marginal costs of certain types of labor go down a lot, entirely new businesses that were cost-ineffective before will emerge. That will create new jobs as well.
What types of skill sets are needed by workers who want to get into AI?
A. While traditional AI requires data scientists with Ph.D.s, generative AI requires a skill set that’s a little more adjacent to the data analytics skills that already exist in the market.
Data analytics relies heavily on certain techniques — data science, data engineering — and almost all AI work, especially generative AI, has a heavy dependence on data.
These are incredibly valuable skills for a world where AI is going to play such a big role. And I think the world needs a lot more people who have them.
0 Comments