AI has been making news headlines lately, and generative AI in particular has attracted a lot of attention. Two of his tools, his ChatGPT, a large language model chatbot, and Dall-E, an image generator, have generated a lot of buzz since being released into public beta in recent months.
You can think of these as today’s cutting-edge publicly available applications of AI. However, both are free to use, which is why their creators, AI research organization OpenAI, are open about the fact that they will have to start making money at some point in order to be sustainable.
When it comes to commercializing AI technology today, companies generally follow one of two strategies. One is to take things slowly, perhaps launching a handful of trials or pilots while taking a “wait-and-see” approach to the organizational, ethical, moral, and social issues converging around technology. ” approach.
At the other end of the spectrum are companies that are “all in.” Companies that take this more aggressive approach invest in smart technology and automation into all their operations, while taking the lead when it comes to answering critical questions.
These all-in companies are the subject of the latest book by two authors who are rapidly building a reputation as authoritative voices in the AI space. Tom Davenport has many appointments including Babson College where he is Chancellor Distinguished Professor of IT and Management, Oxford University Said School of Business Visiting Professor, Digital Economy where he is a Fellow of the MIT Initiative, and Deloitte where he is Senior Advisor to the AI Practice. I am qualified. Meanwhile, Nitin Mittal is Head of Analytics and AI Practice at Deloitte Consulting.
What does “all in” mean when it comes to AI?
The book begins with Alphabet (Google’s parent company) as a prime example of a company “going all-out with AI,” using machine learning to power many of its popular services like Search, Maps, Assistant, and Gmail. I am emphasizing. On the one hand, both authors emphasized to me in a recent conversation that a more interesting area to look at is legacy companies. These are companies (often industry giants) that have embraced and adapted to the AI revolution, not born out of it as is the case with tech giants.
Mr Mittal told me: .
“Unfortunately, not much has been written about how traditional companies have embraced AI. What are they focusing on … companies that have been around longer than Silicon Valley? If so, what are their challenges and motivations?”
Mittal and Davenport decided to look at companies that are making big bets on their ability to create change and value with AI. By their calculations, this elite group makes up less than 1% of the world’s largest companies. why is this?
Davenport tells me: You can’t go “all in” on AI without CEO buy-in. It takes a lot of manpower to do this well.these are [all-in] Companies are hiring data scientists, machine learning engineers, and more.
And, as we said before, it’s essential to have some answers ready for the big questions that someone will definitely be asking you at some point!
If you’re going to focus your business on AI, you have to be ethical about it. Almost all of these companies are doing interesting work in the field of ethics, trying to create responsible and transparent AI and thinking very carefully about how it affects their business. model and strategy. “
Which companies are “all in”?
Companies selected by Davenport and Mittal for their no-holds-barred approach to hiring, among many others, include:
Ping Am – The Chinese conglomerate is deploying AI across multiple sectors, including insurance, banking, transportation and smart cities, but its application within the healthcare sector is of particular interest.
DBS Bank – Singapore’s largest bank, its CEO has publicly admitted that its most important competitors are not other banks or financial institutions, but tech-first giants such as Google and Tencent.
CCC Intelligent Solutions – A Chicago-based insurtech company that combines computer vision and big data analytics to create a system that allows customers to receive near-instant payments based on photos of cars taken after a crash.
Shell – Uses drones and computer vision to create AI systems that can perform pipeline, refinery and infrastructure analysis in weeks that previously took years.
Airbus – Created an ecosystem of AI-based platforms to enable airlines and other partners to optimize flight routes, predict fuel usage and perform predictive maintenance on aircraft.
How do “all-in” companies operate?
During their research, Davenport and Mittal identified three “strategic archetypes” that have often been pursued and adopted by companies that have created real value from AI.
The first is the pursuit of innovation. This means companies are using AI to do new things that neither they nor their competitors have ever done before. Morgan Stanley, which created automated investment tools, and the aforementioned Airbus are two prominent examples here, according to Davenport.
The second strategy focuses on operational transformation. This includes using AI to improve your work. This can range from creating more efficient marketing pipelines, optimizing supply chains, making the most efficient use of physical space, developing smart pricing strategies, streamlining procurement processes, finding the right jobs for the right jobs. It means everything from hiring people better.
Third, top players in AI gaming understand how to use this powerful new technology to influence customer behavior. This includes methods pioneered by social media companies and now practiced in many other industries to separate customers from their data, and wearable and black-box technologies developed by health and auto insurance companies. , including credit scoring and strategies to encourage good behavior.
What can companies learn from an “all-in” AI company?
Perhaps one of the clearest lessons to be learned from this book is that the transformative power of AI is by no means limited to tech-native businesses in Silicon Valley.
The authors also make it clear that many of the challenges to overcome are technical in nature, but by no means all.
Mittal said: AI and related capabilities that your organization needs.
“In traditional organizations, all these aspects are much more important than just implementing and experimenting with technology.”
you can click here Watch a webinar conversation with Tom Davenport and Nitin Mital, authors of All In On AI: How Smart Companies With Big With Artificial Intelligence.
To stay up to date on new business and technology trends, subscribe and follow our newsletter. twitterCheck out my 2022 Business Book of the Year award winner, Future Skills: The 20 Skills And Competencies Everyone Needs To Succeed In A Digital World and Business Trends in Practice on , LinkedIn and YouTube .
Follow me please twitter or LinkedIn. check out My website or some of my other works can be found here.
