Artificial intelligence (AI) and machine learning (ML) are quickly transforming business operations and customer experiences, but not all enterprises are keeping up with the AI trend. Some businesses lag behind because they lack the financial and human resources to develop these tools. Others haven’t yet developed a vision of the AI future, and the extent to which it could benefit their business models.
Regardless of where different businesses currently fall on the AI development spectrum, trends point to a future where businesses will need to accept AI innovations in order to survive. The concept of AI equity has recently entered into greater business technology conversations, with major tech companies discussing how AI can be made more equitable, accessible, and easily understood by the business community at large.
SambaNova Systems is a company that specializes in AI innovations. Marshall Choy, VP of Product at SambaNova Systems, recently shared his thoughts with CIO Insight about how AI development looks now, and how a drive toward AI equity can improve the business technology landscape.
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AI Equity Q&A with SambaNova Systems Executive
The Current State of Enterprise AI Development
CIO Insight: What is the number one mistake you see companies make when they first try to integrate AI into their business model or product offerings?
Choy: A lot of companies should actually look at AI as a strategic initiative across the organization. Usually, they just dip their toes in with a pilot project, then all teams decide to do their own pilot projects, and then there are several disjointed projects.
AI is less effective with these silos of heterogeneity. So it’s important to develop a strategic initiative across departments in an organization.
CIO Insight: How is AI currently changing the world of business? What efficiencies and new solutions come from AI in business?
Choy: AI is revolutionizing business in much the same magnitude we saw the internet do in business technology nearly two decades ago. The nature of software development and IT has changed significantly with AI.
We’re crossing into this new world of machine learning and AI-driven technology. Enterprise resource planning, CRMs, all of those other systems will continue to exist, but there’s a whole new growth wave of tech that’s being driven by AI, like computer vision and natural language processing.
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Larger vs. Smaller Business AI Adoption
CIO Insight: Traditionally, larger enterprises have adopted AI technologies before smaller companies. Why is that the case, and what makes them more successful and quick to adopt these new technologies?
Choy: The tech giants, the industry leaders, the hyperscalers have all the resources from the financial and human resources perspective. And they also have the motivation to keep up with the latest technologies in their hyper-competitive scenario, because of the sheer volume of what they’re trying to accomplish. Their size also gives them a large amount of purchasing power, so they’re able to experiment with new technology and get more purchasing power as a result.
CIO Insight: Can you think of a specific example/use case in which a smaller company developed a successful AI solution? What do you think made them successful?
Choy: In many cases, we hear smaller companies saying ‘I’m a small player, let me pick out a smaller pilot project.’ The successful smaller companies I’ve seen continue to think like big players, and don’t necessarily accept the stratification of AI relative to their size.
A smaller manufacturing customer that we worked with had a particular problem in QA image detection. We worked with them to develop a high-resolution solution with a greater scope, and without manual intervention and additional know-how, their defect detection accuracy increased. This project also improved their end-user safety.
CIO Insight: What industries have traditionally been slow to adopt AI technologies? How do you think it hurts their business and/or their customers?
Choy: The reality is we’re in the early days of AI rollout, so we don’t totally have the data. The thing that I’ve seen that’s slowed down AI adoption is actually less tied to industry and more tied to the digital maturity of the organization. It’s going to be really hard to embrace AI if you’re still doing ERP on an Excel spreadsheet.
Banking and financial services are typically ahead of the curve, but it’s still not uniform across the industry … I think the main point I want to make here is that it’s not too late for anybody in any industry to get on this now, and maintain or gain a leadership position, or become a leader in an industry that has not yet arrived here.
CIO Insight: What is AI equity? What does it mean for the future of the business technology world, and what does it mean to you specifically?
Choy: It’s really about leveling that playing field. To me, it describes the end state of making AI more accessible to a broader user base; offering the AI capabilities of the tech giants without being a tech giant. AI equity means that AI access is not just for the Fortune 10, but for the Fortune ‘everybody else,’ and without the need for the same infrastructure and people resources.
CIO Insight: How are you and SambaNova Systems currently working to create greater AI equity across industries and businesses?
Choy: The reality is that I can think of few industries that build things in piece parts and whose customers expect to self-integrate the solutions and build the end products themselves. Car companies don’t do that, other companies don’t do that, but for whatever reason, that has become the status quo in IT.
At SambaNova Systems, we offer Dataflow-as-a-Service so that organizations of all shapes and sizes can quickly use AI and machine learning services while reducing technical staffing requirements for the solution. We’re automating and integrating things into a single package.
One of the big areas of inequity is in the AI models themselves. The big tech giants have the stacks of PhDs and technical experience to understand these models, but most teams don’t. SambaNova Systems is staffed similarly and does that research, selection, and optimization on behalf of our customers.
CIO Insight: How can other technology vendors encourage AI adoption and greater equity within their customer base?
Choy: It’s all about making the technology easier to use, and maybe more importantly, easier to integrate into what they already have. Not just what’s in the data center, but what’s in the heads of their staff. Companies need to offer solutions that are less vendor-specific, helping their customers to avoid vendor lock-in. Open standards yield more flexibility and choice.
The Future of Business Tech With AI Equity
CIO Insight: How do you think that more widespread AI development could create positive global change? How has the pandemic affected AI and business technology?
Choy: AI is here to oversimplify and automate. Automation is efficiency … let’s take a look at the current pandemic situation. Many pandemic problems are being made slightly less devastating with AI and other patient outcome technologies realized in less time.
I think digital transformation has accelerated, and AI is a big part of that. We’ve talked about digital transformation for a decade now, and a lot of companies who were thinking about it achieved it in less than a year because of the pandemic.
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CIO Insight: What do you think the consequences will be for companies that don’t begin to develop AI solutions in the next few years?
Choy: Just like with the onset of the internet, the companies that adopt AI correctly will be the kings and queens of their industry. And those that don’t could be left behind. The internet completely refactored how apps were written and run and connected people across the globe. Many major enterprises fell off because they were not quick to adopt the internet, and I think AI is going to have the same refactoring effect on future business successes.
CIO Insight: Anything else you’d like to add?
Choy: When [your company] is considering its AI strategy, think beyond the pilots and test drafts. Think beyond the short term toward the long term. Pilots should be experiments on how to use the tech in a broader sense. They should move beyond cross-organizational and application boundaries to get true enterprise-scale benefits … How can you really have a successful pilot if you don’t know what you’re trying to achieve?
Note: This interview has been edited for clarity.
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Marshall Choy is Vice President of Product at SambaNova Systems, responsible for product management and go to market. Mr. Choy brings extensive experience leading global organizations to bring breakthrough products to market, establish new market presences, and grow new and existing lines of business.
Mr. Choy was previously Vice President of Product Management at Oracle until 2018. There, Mr. Choy was responsible for the portfolio and strategy for Oracle Systems products and solutions. He led teams that help deliver comprehensive end-to-end hardware and software solutions and product management operations. Prior to joining Oracle in 2010 when it acquired Sun Microsystems, Mr. Choy served as Director of Engineered Solutions at Sun. During his 11 years there, Mr. Choy held various positions in development, information technology, and marketing.