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Artificial intelligence (AI) is quickly becoming a critical business imperative. No longer a nice to have, AI and machine learning (ML) are a necessary business tool for forward-thinking organizations, helping them make better decisions, create operational efficiencies and improve customer experiences.
In particular, enterprises have widely adopted digital twins—virtual models that simulate reality—over the past several years, allowing them to create digital copies of real-world systems, environments, products and infrastructures for greater operational insight.
Cognitive digital twins—that model individual consumers, businesses, or even national governments—have enabled organizations to explore strategic choices and new business models. And now, as AI/ML technologies have advanced and as the cloud‘s scale and economics have made large computer environments more effective, the use of digital twins has begun to accelerate and expand. Currently, 96% of U.S. based enterprises plan to use AI simulations this year, according to PricewaterhouseCoopers (PwC)’s 2022 AI Business Survey. (Also read: 5 Crucial Skills That Are Needed For Successful AI Deployments.)
While digital twins are used to model and provide detailed, real-time insights into current performance, many organizations want to go further by actually simulating and predicting human behavior in an effort to evaluate future scenarios. They’re doing this by merging scientific computing, industrial simulation and AI to create simulation intelligence built directly into operating systems. The evolution of digital twins into simulation intelligence embedded directly into business analytics and IT systems enables high-speed, macro-scale and multi-scale modeling and ebables the simulation of highly-complex economic, biological, industrial and planetary systems.
Imagine if we could apply the human capacities to evaluate situations on the fly and predictively analyze what could happen next at cloud scale. With a digital twin and simulation, you can explore all possible variations of decisions to find optimal outcomes. You are not gated by the time and cost of experimenting in the real world.
That’s what AI simulation can do for your business.
Operationalizing AI Simulations Today
Once the province of science fiction writers and moviemakers, AI simulations are reshaping the way we do business today in real-world transformative applications. (Also read: Why do AI engineers have to worry about intuitive engines?)
According to the PwC survey, AI simulations are being used to forecast market conditions (57% of AI leaders and 34% of everyone else), enhancing supply chains (54%, 33%), exploring new markets (54%, 38%) and optimizing hiring (39%, 35%).
But AI simulations can go beyond digital twins’ capacity to mirror real-world conditions in the digital realm. Modeling a huge volume of potential scenarios in parallel and applying high-level human-like critical thinking to them allows AI simulation solutions to project likely events and “game out” real-world actions without taking real-world risks—a huge advantage in today’s hyper-competitive, dynamic business environment.
The key to success, however, is the ability to operationalize AI simulations at a scale needed to provide value. This requires businesses to incorporate simulations into their overall analytics architecture and cloud/IT stack, develop high-performing development and production environments that can run in parallel and wield dynamic, scalable hybrid computing capacity.
Here are three business reasons to implement AI simulations this year:
1. To Predict Real-World Scenarios
AI simulations allow organizations to understand people’s and systems’ behaviors, project their future behaviors, evaluate potential changes in their behaviors and gauge the outcomes of those behavioral changes—all in real time.
This can be applied to disease progression, customer behaviors, economic trends and other complex systems. In fact, some companies are using AI simulations to predict how climate change, and the various levels of success the world achieves toward meeting certain sustainability goals, will impact their revenues, costs, and customer attitudes. (Also read: How AI Can Help Tackle Climate Change.)
2. To Explore Business Strategies With Less Risk
Launching a product or entering a new market has always come with risk; but AI simulations can take out some of that risk. That’s because AI can help organizations determine the best business strategy by analyzing how different business decisions are likely to play out.
Currently, 60% of businesses plan to use AI to help formulate their business strategy and 57% plan to use AI simulations to forecast market conditions. For example, organizations have used AI simulations to determine how various levels of 5G adoption in certain markets impact customer behavior and expectations. Organizations have also used AI simulations to predict whether self-driving taxis could take off in particular cities. (Also read: Hacking Autonomous Vehicles: Is This Why We Don’t Have Self-Driving Cars Yet?)
The ability to “game out” various scenarios helps companies formulate business strategy and make real-world decisions without real-world risk. We call this the “gamification of strategy.”
3. To Enhance Customer Experiences
One of the more exciting use cases for AI simulation is delivering high-quality immersive experiences that feel real.
In fact, 61% of companies plan to use AI to improve customer experiences in 2022. Brands are using computer vision, speech and deep learning in the metaverse to interact with customers in new, imaginative ways that help better guide people through the purchasing process—from first touch to post-sale services and support.
The ability to map out scenarios based on real interactions, and predict expected reactions, allows brands to engage with customers with powerful experiences that are helpful, reliable and convenient. (Also read: Gaming, Fashion, Music: The Metaverse Across Industries.)
Transforming Your Business with AI Simulations
AI simulations are transforming how businesses make decisions and operate—giving them the insights into most likely outcomes without actually having to take those risks in the real world.
This allows forward-thinking organizations to determine the impact of evolving situations on their operations, explore business strategies and their likely outcome and enhance customer experiences with human-like intelligence at scale. (Also read: How Digital Transformation Can Bring Resilience During Disruptions.)
The future of AI is here. And it’s exciting.
