Can you trust AI chatbots for financial advice?
More people trust AI chatbots for money advice. This is what we know about their advice.
- Rather than experimenting on the surface, tech companies are effectively investing in and fully integrate AI throughout their operations.
- Clear communication from leadership regarding the role of AI in the company’s future and impact on employees is essential to success.
The tech industry isn’t always getting AI right, but we’ve learned lessons that are good for the rest of the business world to adopt.
For businesses navigating the disruption of artificial intelligence, experts say the way technology companies approach innovation, risk, and organizational change brings important insights.
Tom Davenport, a professor of IT and management at Babson University in Wellesley, Massachusetts, said the most successful tech companies have not only dabbled in AI, but have integrated them throughout their operations. It is a theme he explored in “AI All-in: How Smart Companies Win Big with Artificial Intelligence.”
“Companies like Google and Microsoft have been very aggressive in using AI,” he said. “You don’t want to just tinker with it to get value from it. You have to embed it in different parts of your business and spend a substantial amount of money on it.”
CEOs need to be clear about how AI fits into the company’s future, says Amy Webb, CEO of The Future Today Strategy Group, a New York consulting firm specializing in strategic forecasting. It goes beyond the way it saves money, and how it changes what the company is doing, and what it means for employees.
End-to-end ownership of AI deployments is important.
Davenport said companies are encouraged to assign product managers to manage the entire lifecycle of their AI initiatives. “Someone should oversee the entire process, from conception to implementation and continuous monitoring.”
Tech companies are willing to experiment on their part.
Cultural integrity is just as important as technology preparation, Webb said. Transparency, effective communication, and high-end employees are important to reduce fear and promote buy-in.
And even the best tools can fail without top support.
Webb spoke examples from real life. One of the leadership team’s skeptical executives created so many downstream confusion and fears, fearing that employees had hampered AI efforts and that their work was at risk.
This shows why CEOs must clearly communicate their vision for AI, Webb said.
AI is more than just a technical challenge. It’s a human challenge. Technology has an advantage because its workforce tends to be tech-savvy.
“Today, many tech companies have many (workers) who are more embracing the use of technology, so they are experimenting with AI on their own,” said Thomas Malone, professor of business administration at Patrick J. McGovern, founding director of the MIT Sloan Management School of Management and the MIT Collective Intelligence Center.
“If you’re in an old-fashioned company and no one knows how to spell AI, it’s hard to have them use it,” he joked.
Non-technology companies can work to hone their workplace culture by understanding AI and hiring people at multiple levels, the author of “Superminds: The Superisising Power of People and Computers Think Together.”
Using CHATGPT and other generation AI tools, you don’t need programming skills, so that understanding can be built from within.
“A lot of people can try a lot at such a relatively inexpensive way, and many of them will probably prove useful on a small scale,” Malone said. “Some of them are likely to prove useful on a very large scale.”
Another tip from the world of technology: Protect your AI innovation team from bureaucrats.
Malone said that structural protection against AI innovation is often required with the support of senior leaders. Large business units may be obsessed with the present to focus on the future.
Even if these teams are small, making them higher on the ORG chart gives you the visibility and support you need to explore bold new ideas.
Cultural barriers are realistic. In particular, fear of unemployment and concerns about the unique data leaked into public AI systems. But Davenport said there are private cloud deployments, open source models that companies have full control, or simple solutions that force vendors to commit to not reuse data or prompts.
Experts warn you that you will be fascinated by the latest flashy tools.
“Technology is constantly changing,” Davenport said. “Whatever you buy becomes obsolete quickly.”
In other words, leaders should focus on building core functions (data, people, strategies) that they can adapt.
To navigate change well, leaders need both experimental and production thinking, and Davenport said he will try new things and commit to widespread use of successful pilots.
Ultimately, the AI era is characterized by regulatory, ethical and even technical uncertainty. But experts agree: it is not an excuse for inaction.
“This is not the time to throw our hands away and say, ‘The future is what it is, and we can never affect it,'” Webb said. “Now is the time to make long-term plans, challenge important beliefs, and make better decisions.”
