An Interview with Dr. Tom Corr, Co-Founder, and CEO of AI Partnerships, a network of 125+ AI solution providers.
AIP Interview: With AI being adopted at an astounding rate, CEOs need to seriously consider whether AI enterprise technology is a viable option for their company, product, or service roadmaps. If they already know it is, then there has never been a better time to start developing long-term strategies.
A front row seat to the AI Show
AI, by its very nature, is disruptive. Therefore, AI may threaten your current market share. If your direct competitors are investing in AI to meet their long-term goals, there is a strong probability your company may be left in the dust. If you do survive, you may be following their footprints forever.
Basically, by the time you make a decision about AI, it might be too late. To help CEOs understand this disruptive technology and think about the possibilities of AI adoption, we sat down with Dr. Tom Corr, CEO of AI Partnerships, who has established a network of 125+ companies in AI and emerging technology.
Along with his team, Dr. Corr constantly engages with these companies and therefore has firsthand access to the technology entering the market, insights on the companies currently investing in AI, and the challenges that currently exist in AI adoption. In other words, he has a unique opportunity to see what's happening both from the seller's and buyer's perspectives; he has front-row seats to the AI show.
And now, so do you. Enjoy the interview :)
Q: Tom, you have been full-time in the AI space for 3 years now and worked with 125+ companies in the space. What have been the key takeaways so far?
A: “One of the key takeaways has been that the Covid crisis has provided well-documented important lessons for business leaders.
For example, among the most compelling lessons is the potential that data analytics and artificial intelligence bring to the table. During the pandemic, Frito-Lay ramped up its digital and data-driven initiatives, compressing five years’ worth of digital plans into six months. ‘Launching a direct-to-consumer business was always on our roadmap, but we certainly hadn’t planned on launching it in 30 days in the middle of a pandemic,’ says Michael Lindsey, chief growth officer at Frito-Lay. ‘The pandemic inspired our teams to move faster than we would have dreamed possible.’
The crisis accelerated the adoption of analytics and AI, and this momentum will continue into the 2020s. Fifty-two percent of companies accelerated their AI adoption plans because of the Covid crisis, a study by PWC found. 86% said that AI is becoming a ‘mainstream technology’ at their company in 2021. A Harris Poll found that 55% of companies reported they accelerated their AI strategy in 2020 due to Covid, and 67% expected to further accelerate their AI strategy in 2021.”
Q: What areas have been most active in AI adoption?
A: “AI and analytics became critical to enterprises as they reacted to 2020.
Business leaders understand firsthand the power and potential of analytics and AI in their businesses. They know they need to build a data foundation, taking AI data sets, and putting them into an insights engine using all the algorithms — this is a new experience for some business leaders.
AI is instrumental in alleviating skills shortages. People worry about AI ‘stealing jobs,’ but, ironically, there is an increasingly pressing need to develop AI and analytics to compensate for shortages of skilled labor.
AI and analytics are boosting productivity. The fast-growing cloud computing market has made these innovations accessible to smaller firms.
AI and analytics are delivering new products and services, allowing us to reset the product offerings all the way down to the individual business unit.
AI and analytics are addressing supply chain issues, by helping companies predict, prepare, and see issues that may disrupt their supply chain issues in advance.
AI is fueling startups while helping companies manage disruption. Startups are targeting established industries by employing the latest data-driven technologies to enter new markets with new solutions."
Q: If you were the CEO of a manufacturing company, what would you look to gain from AI adoption?
A: “Although it’s easy to think that artificial intelligence is a thing of the future, AI is already being implemented across the manufacturing industry. AI in manufacturing allows companies to improve demand forecasting and ensure that they are accurately ramping up and down production as necessary.
BMW uses machine learning (ML) models to evaluate images of components on the production line to pinpoint any deviation from standards — in real-time. Another company actively utilizing AI is Caterpillar. They report that their marine division saves up to $400,000 per ship — per year — using Big Data to determine how often the hulls should be cleaned to maximize efficiency.
The implementation of AI in manufacturing is complex and requires the commitment of many parts of the organization.
The first step to implementing artificial intelligence into your manufacturing process is to partner with an experienced vendor to help you analyze your current compute resources and existing data. The data you already have will be used as a baseline, and it will be processed through ML models to determine what trends can be identified.
If you want your manufacturing AI implementation to be truly successful, there must be a specific and measurable problem that you are trying to solve. There must also be data available regarding this problem and a commitment from your leadership to adopt the right tools.”
Q: What would you tell the CEO of a manufacturing company that’s on the fence about AI?
A: “I would tell them that the primary focus of AI in manufacturing is limiting downtime and ensuring that production lines continue to operate effectively. This is one of the best use cases that we are seeing from AI being applied to the manufacturing industry. It will become the primary benefit from AI adoption.
Q: Do you think AI is a must? Can companies survive without it in the near future?
A: “My view is that AI must be considered by companies if they want to remain competitive.”
Q: If management gives the green light on researching AI tech for their company, where should they start?
A: “MIT recently did some research on the steps involved in researching AI implementation at companies that I believe can get your company heading in the right direction. Some of their findings included the following:
Consider the Why
Consider using the technology to enhance your company’s existing differentiators, which could provide an opportunity to create new products and services of interest for your customers and generate new revenue.
Organize for AI
The market is struggling to align organizations around AI. It’s first about developing a shared understanding. Having the proper infrastructure in place is another prerequisite.
Connect AI Initiatives to Organizational Strategy
Finally, organizations now think about AI as a piece of their overall strategy, rather than an add-on to it. One can frame this distinction as having a strategy with AI versus only a strategy for AI.’’
Q: To give other CEOs a heads up on the possible pain points involved with AI implementation, what would you tell them?
A: “There are various potential pain points in implementing AI. Key ones would include:
Having enough Computing Power
Not addressing the internal Trust Deficit of AI within your company
Limited Knowledge of what AI is or how it works
Human-level knowledge that AI is more beneficial to the work than another employee
Data Privacy and Security
The Bias Problem: AI is only as morally good as who trains it
Not enough Supplemental Data to train the model"
Q: As CEOs explore AI, it's important to know what's true and what's false. What are some of the misconceptions you have heard?
A: “There are many misconceptions as to what AI can and cannot do. The ones that are most commonly reported are:
Machines learn by themselves.’
Machines are not yet at the stage where they can make their own decisions about their field of application, and what decisions they do make are grounded in a considerable amount of human work upstream.
‘Machines are objective.’
Nothing could be further from the truth. Often, an AI model reproduces a confirmation bias that it has inherited from its human creators.
‘AI is the same thing as machine learning.’
Machine learning, or the idea that machines can learn and adapt through experience, is only one tool of AI. That said, the concept of AI has no commonly accepted definition and its limits are blurred.
'AI will kill jobs!’
As was the case with the automation and robotization of recent decades, it would be more accurate to say that AI technologies will replace some jobs and transform others. In other words, AI will profoundly change the nature of work, as was the case in previous industrial revolutions, but is unlikely to reduce the overall number of jobs.
‘AI is not useful in my company.’
Are you sure? AI can already improve interactions with customers, analyze data faster, assist in decision-making, generate early warnings of upcoming disruptions, and more. Why deprive yourself of these benefits while theyʻre being realized by your competitors?
‘Super-intelligent machines will surpass humans.’
Today’s AI applications are very context-specific, i.e. they respond to highly-focused problems. Generalized intelligence like human or natural intelligence is not yet on the agenda."
Q: CEOs look at ROI as a main KPI for their company's innovation goals. With that being said, what would you tell CEOs about ROI on AI?
A: “It might be very challenging to develop internal standards, goals, and KPIs inside an AI project but there are a few crucial factors to consider:
Costs – a custom AI system is almost always a significant investment. You need to invest resources to bring you profit.
Savings – sometimes the AI project can generate profit in reduced costs of your company’s daily activities as well as incremental income.
Soft profits – with AI, you can improve your company in countless areas which leads your company to subsequent increased profits.
Goals and KPIs – try to predict the purpose of your project, especially from the financial perspective.
Future profits – very often, the implementation of AI in the company generates new revenue streams.”
Q: Lastly, if a CEO thinks that their company cannot afford AI, what would you tell them?
A: “If you’re ready to enlist AI for your business, there are thousands of ‘plug-and-play’ options already available. My advice is to start small and scale as needed.
Know your budget
Understand the time investment
Find a company that does the training for you and offers ongoing support
Know the problem you hope to solve
Lastly, ask yourself if the AI will integrate with the platforms you’re currently using. (Because free or affordable can become very expensive if this all needs replacing.)”
Now that you have insights from this interview, here's what you can do.
Gather stakeholders from your company and start the conversation. We recommend starting by identifying areas in your business, product, or service that can not only give you the desired outcome but cause more value to be created.
Find out how AI is being adopted in your industry. We focus on manufacturing, healthcare, and finance while also covering agnostic areas such as sales and marketing, data engineering, and infrastructure. AI is being adopted in every industry so there is a chance it's already in yours.
If your organization is starting strategic planning for long-term AI adoption, your next step is finding the right AI partner. It can be challenging to find one so do your research.
Or contact us. We can help.
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