7 business areas ripe for an artificial intelligence boost
Last Updated on by Segun Ayo
Artificial intelligence has captured everyone’s imagination, but what can we expect from the technology? A recent survey of more than 550 executives from IBM finds plenty of support from the top — everyone wants to plunge full-force into AI to increase the speed and capabilities of their businesses. At the same time, AI is still very much in the early stages. More than half of the executives are still either experimenting or testing on a limited basis around their organizations, and one in seven are only at the planning stage.
Before enterprises begin sinking large sums of funds into AI approaches, it’s important to understand where AI can have the greatest impact. In his latest book, The AI Age, Adam Riccoboni, founder of AI consulting firm Critical Future, explores the areas where AI is already making a difference, and where we stand on the AI evolutionary scale.
There are multiple areas of the business that can benefit from AI right now. Riccoboni identifies the key business areas where AI can be applied to enhance or increase capabilities:
Supply Chain Management
- Challenges to overcome: “Enhance visibility, find weak links, match demand with production, manage suppliers”
- What AI will do: “Control software responds automatically to scale supply chains, in response to real or predicted demand. Predictive intelligence anticipates demand. Machine learning, combined with IoT devices and intelligent monitors, automatically flag failing links in supply.”
(AI’s potential in the supply chain is explored more deeply in this recent post.)
- Challenges to overcome: “Discover new customers, find cross-sell/upsell opportunities.”
- What AI will do: “Analytic systems explore existing customer graphs to find new customers. Virtual sales agents can engage with customers.”
- Challenges to overcome: “Design campaigns, track campaign effects, target and personalize advertising.”
- What AI can do: “Rank or cluster existing customers according to interests. Receive reports on campaign effect. Identify lucrative product areas. Capture product sentiment and trending concepts.”
- Challenges to overcome: “Predict maintenance and risks, optimize production lines.”
- What AI will do: “Estimate the probability of failure or time to failure of production components. Machine vision provides automated visual inspections. Personnel systems learn from employee data and past performance to allocate the best available employees.”
- Challenges to overcome: “Prevent cyber attacks, create custom intelligent software.”
- What AI will do: “Predict and prevent maintenance requests. Constantly test deployments with intelligent tooling. Monitor network traffic and topologies.”
- Challenges to overcome: “Identify talent, conduct interviews, review performance.”
- What AI will do: “Explore social/business networks such as LinkedIn and compile candidate lists with graph-processing AI. Process internal communications with sentiment analysis tools.
- Challenges to overcome: “Report trends, fraud detection, credit risk, reviewing contracts.”
- What AI will do: “Filter and refine voluminous financial reports. Predict and flag developing issues, such as unexpected losses, spiraling budgets, or cash flow problems. Virtual finance agents communicate with suppliers.”
But AI means much more than simply boosting intelligence within narrow bands of business functions. Ultimately, it means new ways of doing business. The AI revolution will move through four stages, and we are just moving into the second stage, Riccoboni states. Here’s what to expect as the AI revolution unfolds:
- Internet/Business AI: We are already will into this stage, Riccoboni asserts. And, as the above-mentioned IBM study shows, at least half of businesses are at least experimenting with AI on some level — 85% of top executives see AI as a business imperative.
- Perception AI: “Perception AI is all about machines beginning to ‘see’ the world,” Riccoboni says. “Before, AI machines were deaf and blind. Machine could not interpret audio and visuals. From a technology perspective, AI already has the ability to see, speak, hear and much more. The next wave of AI will revolutionize how we experience and interact with our world, blurring the lines between digital and physical worlds.”
- Autonomous AI: This is not to be confused with automated AI, Riccoboni says. “Autonomous AI can learn and act on its own with self-agency. Current robots are automated, because they can repeat an action, but they can’t make decisions or improvise. But as machines develop — and Perception AI along with sight, touch and optimization from data develop — machines will become especially useful.”
- Human-Level AI: This is the ultimate progression of AI, which is actually Artificial General Intelligence, or AGI — in which machines will reach “superintelligence” in which they will be able to comprehend and act on problems with blazing speed. We still have a long way to go, as AI as we know it is currently in the realm of “narrow AI,” Riccoboni explains.
Finally, Riccoboni provides some career guidance for professionals seeking to build careers in the AI age. While there are many opportunities arising as a result of the growth of AI — AI systems development and data science, for example, Riccoboni advises professionals to focus on being generalists, not specialists, to prepare for this new world. “Human creativity is an area of comparative advantage over AI because of its generality. Empathy is a narrow skill, so AI can be trained to do it. But when empathy means being able to connect the dots across domains, machines cannot master this… Instead of learning narrow technical skills, we need versatile, cross-domain, generalist skills.”