AI has evolved from a futuristic sci-fi concept to a real-world instrument with almost limitless implications for our everyday lives, careers and businesses. Microsoft Chairman and CEO Satya Nadella referred to AI as “one of the most transformative technologies of our time.” In his 2023 annual shareholder’s letter, he said, “This next generation of AI will reshape every software category and every business, including our own.” In 2024, Microsoft research found “as much as a 70% improvement in productivity using generative AI for specific work tasks.”
As business leaders facing one of the fastest and most critical technological shifts of our lifetimes, it is important to understand and implement AI to drive impact and ROI within your organizations, teams and products. Businesses can gain a competitive edge when AI is used to automate repetitive tasks, analyze vast datasets for actionable insights, personalize customer interactions and services, and optimize workflows in ways that human efforts alone cannot match.
Research by NVIDIA demonstrates these impacts. In telecommunications, 67 percent of surveyed companies saw revenue growth from implementing AI tools, with 19 percent reporting gains of over 10 percent. In financial services, 43 percent reported that AI has created operational efficiencies and 42 percent reported that AI created a competitive advantage. In retail and consumer packaged goods, 69 percent of companies experienced revenue growth and 72 percent experienced reduced costs.
According to a recent report from Menlo Ventures, 72 percent of decision-makers anticipate broader adoption of generative AI tools in the near future, but more than a third of respondents said they didn’t have a clear plan yet of how to utilize AI. McKinsey reports that AI adoption increased from 20 percent of companies in 2017 to 72 percent in 2024. From 2023 to 2024 alone, there was a jump from 55 percent to 72 percent. This led McKinsey to dub 2023, “The year the world discovered generative AI.”
Clearly, AI has significant potential across industries. This creates an ongoing imperative for business leaders to decide what, where and how to implement AI solutions. As AI technology advances and improves, leaders must reassess their operations, processes and tools, finding new ways to unlock value.
Every business can use this technology to meaningfully augment work, creating more efficiency, insight and productivity. But, specifically, how can leaders take AI’s capabilities and turn them into business successes?
This article is the first in a series that will help business leaders become more familiar with AI, find and evaluate potential next steps in their AI strategies, and develop realistic implementation plans. In this first article, we introduce a new framework called the “AI Decision Cascade,” intended to help business leaders and organizations formulate an AI strategy, regardless of past experience with AI.
Understanding your AI maturity
Before tackling frameworks and strategy, leaders need to understand where their business currently sits in terms of AI sophistication. Some departments and teams may not understand the technology at all, while others may have several successful implementations under their belts. PwC reported that 61 percent of leaders who have adopted AI cannot explain how their AI-powered decisions are working. By first understanding the situation, leaders can avoid wasted effort and focus on success.
Leaders can also avoid wasting employee efforts by ensuring a targeted approach to AI implementation. Early adopters of AI within leadership or employee teams may drive singular AI initiatives with some success, but the lack of cohesion in this approach can lead to confusion and fragmented applications across the organization. With the “AI Decision Cascade,” leaders can quickly decide which new ideas for AI adoption should be the highest priority, making it easier to create a cohesive and ongoing strategy for implementing AI.
The “AI Decision Cascade”
The “AI Decision Cascade” is a robust framework for leaders looking to articulate an AI strategy for their organization more fully. This type of framework is based on the “Strategic Choice Cascade” from A.G. Lafley and Roger L. Martin’s book “Playing to Win.” This framework has been modified to help business leaders develop an AI-specific strategy that integrates well within the unique context of their organization.
As leaders work through the questions in the following cascade, they will likely find that the answers to previous questions need to be modified. Like other decision cascade frameworks, using the framework is an iterative process that should help drive toward a cohesive and realistic set of next steps. By ensuring that answers connect back to the organization’s strategy, mission and values, leaders can guarantee their efforts drive toward their ultimate goals and maintain a consistent narrative.
What is possible with AI
The first element of the framework requires leaders to understand the benefits of AI and how it can help their organization. This step will help leaders identify meaningful use cases that align with their strategic goals later. The following are areas where AI can drive significant organizational value.
Automation
AI has revolutionized automation by taking over routine tasks and complex processes that previously required human intervention. From data analysis to process automation and predictive maintenance, AI can often handle high-level functions accurately and quickly. This ultimately leads to many other potential impacts included in this list.
Productivity gains
AI optimizes production and operational workflows. It can help identify inefficiencies, complete repetitive or time-consuming tasks, predict maintenance needs, and automate decision-making processes. AI can also help reduce the time spent by employees on research, content generation and product development.
Reducing costs and mitigating risks
By streamlining operations, AI reduces manual labor costs. In addition, AI can enhance the quality and consistency of outputs, reducing risk and costly errors that lead to reduced revenue. For example, AI can provide predictive analytics that prevent downtime, automate customer service and reduce staffing needs. AI helps companies lower operational expenses while maintaining or even improving service quality. AI can also proactively monitor cybersecurity threats and be a valuable tool in risk management.
Analytics and decision support
AI excels in processing vast amounts of structured and unstructured data in real time, generating actionable insights from patterns that could otherwise be missed by human analysis alone. These insights empower leaders and employees to make more informed, data-driven decisions that enhance performance — leading to better business outcomes. In some cases, AI can be utilized when moving away from older SaaS systems toward AI-powered smart systems that can actively track vital information, proactively provide insights, and add value to static datasets and systems of record.
Communication and knowledge support
AI-driven communication tools, such as chatbots, virtual assistants and collaboration platforms, enhance internal and external communication by providing real-time support, ensuring consistency and reducing miscommunication. AI can also automate routine responses, manage scheduling and facilitate coordination across teams, optimizing the flow of information.
Whether you are an AI newcomer or veteran, all organizations can benefit from the “AI Decision Cascade” as they continue on their AI journey.
The sooner companies put their next steps into motion, the sooner they can capitalize on AI’s transformative potential. With AI evolving rapidly, waiting means missing out on critical opportunities. As its capabilities expand, leaders who act decisively now will gain immediate advantages and position their companies to catch the growing wave of AI advancements. The future belongs to those who move quickly and strategically. By leading adoption with your organization, business leaders can ensure their organizations thrive in an increasingly AI-driven world.
Our next article will examine the second element of the “AI Decision Cascade” framework: helping business leaders decide where to implement AI in their organizations.
