By Stephen DeAngelis
Futurist Bernard Marr observes, “As a species, humanity has witnessed three previous industrial revolutions: first came steam/water power, followed by electricity, then computing. Now, we’re in the midst of a fourth industrial revolution, one driven by artificial intelligence and big data.”[1] He adds, “I like to refer to this as the ‘Intelligence Revolution.'” The intelligence revolution is necessary thanks to the enormous amount of data being generated each day and the speed at which events unfold in today’s computer-driven world. Marr notes, “AI gives intelligent machines (be they computers, robots, drones, or whatever) the ability to ‘think’ and act in a way that previously only humans could. This means they can interpret the world around them, digest and learn from information, make decisions based on what they’ve learned, and then take appropriate action — often without human intervention.” The revolutionary business environment described by Marr is one reason Enterra Solutions® is focused on advancing Enterra Autonomous Decision Science™ (ADS®). ADS is the next step in the journey beyond data science. Using ADS, the machine plays the role of the data scientist or subject matter expert to help optimize a business and help it run at the speed of the marketplace. As a result, organizations can quickly make decisions that take advantage of market opportunities. Marr explains, “I guarantee your business is going to have to get smarter. In fact, every business is going to have to get smarter — from small startups to global corporations, from digital-native companies to more traditional businesses. Organizations of all shapes and sizes will be impacted by the Intelligence Revolution.”
Getting Smarter During the Intelligence Revolution
Rajeev Dutt, CEO of AI Dynamics, agrees with Marr that companies need to get smarter and learn to leverage artificial intelligence. However, he is not sure some companies are ready to make the transition. He explains, “If you haven’t implemented an artificial intelligence solution into your business yet, you may feel like you’re missing the boat. And in many ways, I’d agree with you. But is your business ready for artificial intelligence? Some studies show that nearly 99% of companies are investing in AI in some way, shape or form. AI isn’t a ‘will we, won’t we’ type of technology. AI will be the de facto standard, much like an operating system or software, it will be embedded into every business technology in the not so distant future. But that doesn’t mean you should just jump on the bandwagon for fear of falling behind. There are a lot of considerations to take into account before even dipping your toes in the AI water — or to carry through on my first analogy, to ensure you aren’t putting the cart (or bandwagon) before the horse.”[2] To ascertain whether your company is ready to make the leap, Dutt suggests asking a few questions: “What is the business opportunity? Do you have the resources you need to implement process transformation? Are there security implications? What data do you need to solve the problem and what will you need to acquire it? And maybe most important, are there any ethical implications for implementing an AI solution?”
The staff at the Economist Intelligence Unit (EIU) agrees with Dutt that understanding the business opportunity is of utmost importance. They explain, “[It is essential that companies adopt] a digital transformation strategy — and AI is a critical part of that process. The technology is developing rapidly, but it remains important for businesses to understand why they want to use it. That business need will then drive the necessary investment and innovation in the right direction, with fewer missteps.”[3] Dutt suggests a few preliminary steps to take before implementing the AI portion of a digital transformation strategy. First, understand what artificial intelligence is good at, and what it isn’t. Second, have a well-defined problem. “You need to consider what is the problem and why you are trying to solve it.” Third, identify the performance criteria for AI (i.e., identify what success looks like). Fourth, determine the team and technology capability. Finally, understand the long-term impacts. Dutt notes, “AI is simply not understood by most people in the organization and even framing a business argument for deploying AI is not always clear. Obviously, a clear understanding of ROI will help but even this isn’t enough because in the end, like any other technology deployment, the ROI has to be compared to other non-AI alternatives.”
To help clients become intelligent enterprises, Enterra® developed the Enterra System of Intelligence®. This system ushers in a new era of AI-enabled management science by merging cutting-edge analytical techniques with a business’ data and knowledge to Sense, Think, Act, and Learn® on enterprise data to meet the changing needs of the market. Enterra’s system acts as central “brain” within an organization, ingesting diverse datasets, business logic and practices, and strategy, to uncover unique insights and generate autonomous recommendations across the enterprise at market speed. Insights and recommendations generated by the Enterra System of Intelligence are acted upon through deep integrations with an organization’s established systems of record and engagement, akin to how the brain (decision-making) and central nervous system (actions) interact within the human body. Enterra’s system uniquely learns the environmental reasons that recommendations are successful or not and persists that learning in its Ontologies and Generative AI knowledge bases to improve future insights and recommendations. You can watch a concept video by clicking on this link.
The EIU staff notes that many of today’s leading companies are already taking advantage of AI in the logistics and retail space. They report, “Amazon (US) has been using AI for predictive logistics for several years now, having patented the technology back in 2014. The online retail giant analyzes customer data in order to predict demand for goods, so that it can prepare and ship products for delivery within just a few hours of purchase. Retailers such as Walmart (US) use AI tools to predict and plan inventory levels, not just by analyzing demand but also by scanning pictures and video from store cameras. Consumer companies use AI and geolocation data to improve transparency in their supply chains, for example to meet their sustainability targets; Unilever (Netherlands) uses this to track deforestation. Another use case for AI (especially generative AI) is in customer service, with many businesses using AI-powered chatbots to address customer queries, or even to take orders or help them shop.”
Concluding Thoughts
Although many companies have shown interest in leveraging artificial intelligence, journalist Meaghan Yuen reports, “Most companies worldwide either haven’t adopted AI and machine learning yet or are still in the research phases. In North America, 42% of companies haven’t implemented AI or ML, while 22% are rolling it out and 21% are scaling up the technology, according to a June [2023] Workday survey.”[4] Back in 1972, Alka Seltzer ran a campaign using the phrase “Try it, you’ll like it.” The idea was that people who tried different foods didn’t always “like it” and needed to take an Alka Seltzer to counter the consequences. With careful planning and proper preparation, companies who try AI will like it — and they won’t need to take any Alka Seltzer.
Footnotes
[1] Bernard Marr, “What Is The Artificial Intelligence Revolution And Why Does It Matter To Your Business?” Forbes, 10 August 2020.
[2] Rajeev Dutt, “Is Your Business Ready for Artificial Intelligence?” Readwrite, 28 August 2020.
[3] Staff, “How companies use artificial intelligence,” Economist Intelligence Unit, 5 June 2023.
[4] Meaghan Yuen, “Many companies worldwide have yet to adopt AI and machine learning,” EMarketer, 18 October 2023.
