Imagine having a crystal ball that could show you the outcome of every decision before you make it. In L&D, scenario simulations are the closest thing we have to that magical crystal ball. By simulating real life scenarios and predicting outcomes based on the decisions made by the learner, AI-powered simulations allow us to play in the gray, evaluate different strategies, fail forward, and try again—to achieve the best possible outcome.
As it stands right now, there is no CrystalBall 15 Pro available for purchase. Instead, we must live with the choices we make and the outcomes that follow. Business leaders face increasing pressure to make the right decisions in the workplace. Competitive markets, rapid technological advancements, evolving consumer preferences, and global economic uncertainties create a complex maze of options and uncertainties for leaders to navigate.
According to research by Oracle and Seth Stephens-Davidowitz, decision stress (regretting, feeling guilty about, or questioning decisions made in the past year) is a reality for 85% of business leaders—this while 75% of them have seen their daily volume of decisions increase tenfold over the last three years. So the need to develop effective decision-making skills and behaviors has never been greater.
The challenge is that decision-making skills are tough to hone—and with traditional methods, learners revert to old behaviors soon after they return to the demands of the real-world. In response, more and more businesses are turning to AI-powered technologies to help develop their employees’ decision-making skills. Deloitte named the top five benefits of implementing AI in an organization, and helping leaders make better decisions was one of them.
But how exactly does AI work its magic?
Assessing success through AI-powered scenario simulations
AI use cases extend across various decision-making domains:
- Leadership dilemmas
- High-value sales and negotiation scenarios
- Tribal knowledge transfer
- Business acumen challenges
- Data and analytics quandaries
- Having difficult conversations
- And many other unique business performance challenges
Learning in the trenches
Learning by doing is the mantra of effective decision-making training. AI makes this possible through unscripted dialogue that allows learners to engage in realistic, real-time, flexible conversations that mirror workplace challenges. From customer service to leadership to healthcare, immersive simulations allow learners to experience real-world scenarios and evaluate their decisions under pressure.
Making the decision is one thing, but real transformative learning comes in the form of immediate feedback that allows learners to reassess, reconsider and adjust their strategies on the fly. We can leverage GenAI to simulate highly contextualized real-world scenarios and evaluate the outcomes of different choices, allowing learners to gain real-time insights into the potential impact of their decisions.
Blueline’s ExperienceBUILDER platform uses generative AI as an engine to simulate a broad range of decision-based business challenges, allowing learners to experience the impact of their decisions in the moment. Custom scenarios can reflect your organization’s unique workplace challenges. AI assistants can be designed and developed to reflect common personalities. And meta-analysis and scoring assistants can evaluate how well a learner is responding based on predefined best practices that support business processes and standards.
Let’s take a look at an example from our demo
The situation: I am given an opportunity to meet with cross-functional team leaders representing, sales, marketing, IT and HR. I need to do my best to communicate that we need to launch our next software product two-quarters faster than originally projected and secure their buy-in:
Each team member then provides unscripted responses (within the bounds of guardrails created using advanced prompt engineering):
Now, it’s time to make an important decision! After reviewing each of the team leader’s responses, who should I meet with first? Do I prioritize them based on their initial reactions? Or do I organize based on business function? The choice is all mine.
While I will have the opportunity to discuss each of the team members’ concerns, I determine that Sarah, the HR lead, should be my first discussion. This time, I’m able to engage with her in a back-and-forth discussion and unpack the issues she feels are critical to her team’s success:
Phew, it looks like I was able to quickly address one of the core issues Sarah raised. Once I finish my conversation with her, I receive a comprehensive analysis of how effectively I handled our interaction and how my responses impacted her. I receive specific feedback about my tone, style, word choices and how well I addressed the business issues at hand.
Despite our best efforts, this explanation doesn’t begin to do justice to the power of our AI enhanced ExperienceBUILDER platform. I highly recommend scheduling a demo so you can experience it for yourself.
Better business decisions are a phone call away!
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