Article

Adoption to ROI: Leading Business Transformation With AI

IEEE Rutgers Mini MBA AI

Summary: As AI adoption accelerates, organizations need functional leaders with the skills to turn generative and agentic tools into measurable business value. Moving from productivity gains to tangible impact requires the ability to identify workflow inefficiencies, evaluate AI opportunities, lead process redesign, and align initiatives with strategic goals. These capabilities are essential for organizations seeking to transform AI investments into a long-term competitive advantage.

Across industries, organizations are investing heavily in AI tools, platforms, and talent. They hope to gain efficiency, make more informed decisions, and unlock new growth. The level of investment is significant. A recent survey of 2,400 knowledge workers and C-suite executives found that 59% of organizations invest at least US$1 million annually in AI technologies, while 97% of executives deployed AI agents during the past year.

It’s become clear that business leaders are no longer hesitant to deploy AI. However, the real question today is how to turn these deployments into measurable outcomes. To truly gain a competitive edge as these tools evolve, organizations need functional leaders who treat AI as a catalyst for transformation rather than a simple productivity booster.

Time Saved ≠ Dollars Earned

While widespread AI adoption can result in time savings per employee, it doesn’t necessarily translate into big-picture impact. A marketing manager who saves a few hours per week drafting content may become more productive, but their organization’s operating model remains unchanged. Likewise, a financial analyst could use AI to summarize reports more quickly, but this small efficiency gain does little to improve the bottom line.

Many organizations are struggling to connect the dots between their initial AI investment and true operational impact. According to McKinsey’s State of AI data survey, 64% of participants said that AI enables innovation, yet only 39% reported an impact on operating profit at the enterprise level.

Why AI Deployments Fail to Deliver

When an AI initiative doesn’t produce the promising results that were first envisioned, many blame technology by default and go straight back to the drawing board. In fact, nearly 50% of generative AI projects were abandoned last year due to poor data quality, inadequate risk controls, escalating costs, or unclear business value.

With any AI rollout, it’s vital for business leaders to remember that they’re not just solving technical gaps, but also larger organizational challenges. Many deployments fail because teams try to layer AI onto old tools instead of redesigning the workflow. Legacy processes, silos, unclear governance, and resistance to change all create significant barriers to realizing AI’s full potential.

Those who have achieved successful business outcomes with AI recognize that a deployment is an opportunity to rethink how work gets done, rather than to optimize how it currently gets done. To unlock this level of transformation, business leaders must understand how AI’s capabilities can go beyond simple automation to reimagine operations.

How Functional Business Leaders Can Lead AI Transformation

Companies frequently frame AI deployment as a project for IT teams alone. However, 53% of executives feel IT teams aren’t delivering real value with generative AI. While technology clearly plays an essential role in building and maintaining AI infrastructure, it takes a real understanding of business operations to lead transformation.

Business leaders and non-technical teams are uniquely positioned to identify how AI can add value, drawing on a deep understanding of workflows, bottlenecks, handoffs, and inefficiencies:

  • Finance leaders can optimize forecasting, variance analysis, and financial planning workflows
  • Supply chain leaders can leverage predictive analytics to improve inventory management, demand forecasting, and logistics 
  • Customer experience teams can redesign service operations around agentic AI
  • Operations leaders can identify opportunities to reduce manual work and streamline cross-functional processes

When functional leaders work together to build new frameworks, their collective expertise becomes a force for impact at the enterprise level, rather than incremental efficiency gains for individuals or a single department.

The Gap Between Business Knowledge and Technical Expertise

With countless AI tools on the market, it’s easy for organizations to keep stacking them onto their existing tech stack. But getting the most out of your investment means choosing the right tools, not more tools.

Many businesses struggle to identify how AI can actually benefit them, with a recent study reporting that 75% of executives admit their AI strategy is “just for show.”

Translating AI capabilities into measurable outcomes requires strategic thinking, operational expertise, and in-depth organizational knowledge to identify where value can be added.

This presents a significant skills gap. Functional leaders understand their teams’ needs, yet relatively few professionals have the combination of business, analytics, and technical knowledge needed to successfully lead AI transformation at the enterprise level.

Become A Leader for AI-Driven Transformation

As AI innovation accelerates, the organizations that succeed will be those that most effectively convert capabilities into measurable results. Currently, only 20% of companies capture 74% of all AI-driven value, according to PwC’s 2026 Global AI Performance Study.

This presents a major opportunity for leaders who can:

  • Identify value leakage
  • Redesign workflows
  • Lead organizational change
  • Align AI initiatives with measurable business goals

The IEEE | Rutgers Online Mini-MBA: Artificial Intelligence is designed to empower non-technical business professionals with the expertise needed to translate AI capabilities into measurable outcomes. Over 12 weeks, participants gain a practical understanding of AI, its impact on core business functions and the knowledge to evaluate, implement and scale AI initiatives across their organization.

The curriculum combines strategic frameworks with real-world applications. As a result, learners develop the skills to identify opportunities, collaborate with technical teams, and build a roadmap for AI-driven transformation. The program equips leaders to move beyond experimentation and turn AI investments into a competitive advantage.

Discover how you can enroll as an individual or connect with a dedicated IEEE content specialist to enroll your employees in the upcoming September cohort. Learn more and take the next step before the 11 September enrollment deadline.

More Upskilling Opportunities from IEEE

Advance your career with the IEEE | Rutgers Mini-MBA for Engineers and Technical Professionals. This unique program bridges the gap between business and engineering, helping technical professionals grow in their careers. Learn from top experts and enjoy a flexible, self-paced format. IEEE is proud to partner with Rutgers University and UnitelmaSapienza for a special session in November 2026 focused on targeted training for students and professionals. Learn more today!

 

Thursday, 18th June 2026