“Generative AI is one of the best augments, not a substitute or an augmentation. We will hire more advisors.”
When I asked Nitin Mittal, who is leading the new generative AI practice within Deloitte Consulting, how generative AI is impacting white collar workers around the world, he said: His point was that AI provides an enhancement layer rather than replacing those jobs.
But others are starting to make other claims. Of particular note is AI pioneer Jeffrey Hinton, who told The New York Times that AI “removes the mundane work” but may soon “take away much more.”
Hinton has just left his executive position at Google to discuss further. he is a condition “The Danger of AI” Another technology leader who recently hinted at the impact of AI on the job market is IBM CEO Arvind Krishna. He told Bloomberg that his AI could “easily” replace about 30% of his workforce within five years.
To be fair, Mittal himself recognizes that AI may not be purely expansive in the next few years.
“Is it possible that over time we might see some kind of replacement?” he said. absolutely. “
But once “alternatives” begin to occur—that is, when AI takes over certain skill sets—“locks, stocks, barrels,” as he puts it—certifications and regulations are needed to protect consumers. pointed out that it was necessary.
Either way, Deloitte customers are not looking for alternatives right now. The current focus of Mittal’s new generative AI practice is purely on augmentation. He said there was sudden demand from Deloitte clients for his GenAI assistance this year, and a new practice led by him was created (in just two months) to meet that demand.
Deloitte isn’t the only “Big Four” business consulting firm to jump on the generative AI trend. Last week, The Wall Street Journal reported that PWC “plans to invest $1 billion in generative artificial intelligence technology in its U.S. operations over the next three years.”
Impact on IT
One of the direct impacts of generative AI in the enterprise is through the IT department. Not only are developers now commonly using AI-assisted coding tools such as GitHub Copilot, but IT departments face a potential massive disruption to their tech stack.
Mittal believes generative AI will lead to a fundamental redesign of IT. He explained that IT departments need to prepare for a new area called LLMOps, the operational side of large language models (LLMs). This includes continuously updating datasets, intuitively training models, and generating desired modalities, he said.
He also stressed the importance of having guardrails in place to mitigate the risks associated with LLMs.
More broadly, he believes IT needs to shift its focus from its traditional role of implementing systems and building a workforce around those systems. Instead, IT gets into the business of LLMOps to “build models at a rapid pace, deploy those models, train those models, and as a result maintain these models across the organization.” We need to focus on what we do, because these models will inevitably spread across all organizations.” The business functions, workflows, processes, and customer interactions that are relevant to that company. ”
middle layer
I believe that some business intelligence companies and data intelligence companies believe that the data LLM ingests needs to be cleaned and prepared, i.e., as Alation co-founder Aaron Kalb told me, the data is I noticed that it claims that “when trash comes in, trash comes out.” Last interview.
Mittal does not accept it. He believes there is still debate about whether middle tiers such as business intelligence and data intelligence are necessary. Presumably, increasingly sophisticated models will be able to process raw data streams, he suggested. One way he does this is by basically predicting what data is missing. Generation AI does this anyway. There is a growing trend towards “synthetic data” solutions that do just that.
Example of use
So what are some early use cases for generative AI in the enterprise that Deloitte is considering?
Mittal mentioned companies working on proof-of-concept trials in the healthcare sector. [proof-of-concept] Generate accurate billing codes from electronic medical records and doctor notes. Another example is banks. Banks are looking to leverage the speed and low cost of generative AI to handle customer interactions, such as converting chats to emails or serving customers via chatbots.
Mittal argues that these examples show how generative AI can be used to power a variety of professions, such as healthcare and banking, to improve productivity and efficiency.
What skills do IT departments need?
One profession that is sure to be in demand in the near future is prompt engineering, but the field is still being defined. I asked Mittal what background and skill set his GenAI team at Deloitte has.
He replied that his team is off to a year-long head start in generative AI, but needs to train existing employees to become agile engineers. Finding and hiring talent has never been easier. He explained that rapid engineering requires the ability to ask the right questions, be curious, learn quickly, and analyze problems creatively.
He added that a strong background in STEM and experience in software development is still required when it comes to building and refining large language models.
