Tips for achieving AI transformation: What eight business leaders want you to know

AI’s evolution from a buzzy trend to a business investment has surprised many executives. With 65% of companies regularly integrating GenAI into their operations, a figure nearly doubled since 2023, the pressure is on. But while adoption is soaring, the path to success has its fair share of challenges. 

Many organizations still struggle to move beyond the excitement of AI’s potential and translate it into tangible business outcomes. This is because successful AI transformation goes beyond adopting the latest shiny tool. It requires a strategic vision, a robust execution plan, and alignment with broader business objectives.

How can organizations drive AI innovation in an impactful and scalable way? Below, eight business leaders share their insights.

1. Be mindful of ethical considerations when embracing GenAI

Larry Fitzpatrick, Executive Vice President and CTO at OneMain Financial, asks executives to take the ethical considerations of deploying GenAI seriously.

Unlike traditional AI, generative models often operate in a black box, where their decision-making processes can be opaque and difficult to explain.

Larry advises companies not to deploy GenAI directly to customers without human oversight — the potential consequences are too high, particularly for highly regulated industries like financial services, life sciences, and healthcare.

While GenAI presents clear benefits for data analysis and document processing, its unpredictable nature requires strict guardrails. According to a McKinsey report, 44% of organizations have experienced negative consequences from using AI, with inaccuracies and lack of explainability being significant challenges.

Organizations undergoing an AI-led digital transformation must ensure GenAI is used responsibly and aligned with ethical standards. Human oversight remains crucial to building trust and ensuring the safe integration of GenAI into business operations.

2. A strategic approach to GRC is a must

William Reyor, Director of Security at Modus Create and co-author of Defensive Security Handbook, 2nd Edition, emphasizes that overlooking governance, risk management, and compliance (GRC) can expose organizations to significant risks, including financial loss, reputational damage, and compliance violations.

As AI-led digital transformation and adoption accelerates, William says, businesses must take a strategic approach to GRC to navigate the complexities of integrating AI into operations.

AI governance sets the foundational rules, ensuring alignment with organizational values and regulatory frameworks.

Risk management, on the other hand, requires proactive identification and mitigation of AI-related risks, such as unintended system behaviors or data breaches.

Compliance is critical, especially with new regulations like the EU AI Act, which mandates stringent controls for AI systems to ensure safety, reliability, and ethical usage across sectors.

William’s guidance is especially relevant as 42% of organizations report improved data security following the overhaul of digital product implementations, according to our research on digital transformation & product development.

By adopting a strategic GRC approach, businesses can ensure that their AI initiatives are secure, compliant, and capable of fostering trust, giving them a competitive edge in the AI-driven future.

3. Put customers at the center of your AI digital strategy

AI’s power lies in its ability to transform customer experiences, yet many organizations focus solely on efficiency and productivity. Sarah McCasland, Chief Strategy Officer at Modus Create, emphasizes that the most successful AI strategies prioritize customer needs from the outset.

According to our original research on digital transformation & product development, 44% of organizations planned to invest in the launch of new customer-facing applications or features in 2024. We expect this trend to hold in 2025.

To put customers at the center of your AI-led digital strategy, Sarah suggests companies should ensure that AI is fully embedded into their digital products from the concept phase. This approach avoids making AI a last-minute addition and instead enables it to drive innovation and enhance the user experience, meeting evolving customer expectations.

One solution Sarah proposes is collaborating with your data and UX teams and evaluating how your customers interact with your products. This will provide valuable insights into how AI can improve the user experience, ensuring that it serves as a strategic enabler rather than an afterthought.

4. Change management is critical to AI innovation

Your employees may resist AI-led digital transformation, fearing their jobs—or entire departments—will become obsolete. While a percentage of the workforce might fall to a reduction in force, the World Economic Forum forecasts the creation of 97 million jobs due to AI. AI can be a tool to increase employee productivity, cutting out tedious, repetitive tasks in favor of more strategic projects. But you need your employees to understand the benefits of AI initiatives.

Jay Jayamohan, Executive Director of the Center for Innovation & Entrepreneurship at Harrisburg University, stresses that change management is one of the most critical aspects of innovation.

Jay suggests communicating the benefits of your initiatives effectively to avoid pushback from team members. Having a change agent develop communications and messaging about AI in your organization to educate employees and set expectations is essential to ensuring initiatives roll out smoothly. 

5. Prioritize AI use cases with the potential for high ROI

In the rush to adopt AI, many companies overlook a key factor: ROI. Scott Snyder, Chief Digital Officer at EVERSANA, talks about the importance of measuring the ROI of AI initiatives early on.

To ensure successful AI transformation, Scott encourages organizations to carefully prioritize use cases that offer the potential for high returns, such as automating time-consuming processes.

For example, if you do a lot of in-house development, Scott suggests exploring tools to help with code development and code review.

Gartner predicts that 80% of enterprises will have used Gen AI APIs or deployed Gen AI-enabled apps by 2026. However, only those who approach AI strategically, with ROI in mind from the outset, will reap the full benefits.

By keeping an eye on ROI and aligning AI efforts with business goals, companies can ensure that their AI investments pay off.

If you work in life sciences, our in-depth guide to scaling AI in the industry covers the specific use cases, challenges, and strategies relevant to pharma and biotech organizations.

6. Don’t hop on the AI hype train without a clear strategy

According to Pat Sheridan, former CEO at Modus Create, AI should augment and support existing digital initiatives, not be an isolated investment. Without aligning AI with broader business objectives, companies risk wasting resources and failing to deliver real value.

Our research on digital transformation & product development reveals that almost one-third of decision-makers believe the lack of a digital strategy is a top challenge to the overall success of their organization.

Pat suggests organizations start with the problem they’re trying to solve and evaluate how AI can help improve the customer experience, increase efficiency, or future-proof the business. Leaders must be able to address three important questions in their AI strategy:

• How much should I invest to keep the lights on and maintain business as usual?
• How much should I invest to fend off disruption from new players?
• How much should I invest to gain a competitive advantage in my industry?

Instead of blindly jumping into AI initiatives, businesses should carefully assess whether the technology truly supports their strategic goals. Gaining clarity on these questions ensures AI adoption delivers measurable impact.

There’s no doubt that AI is essential for all enterprises in the next chapter of digital transformation. It can enable next-level advances in productivity and innovation. Still, it’s important not to jump on the hype train and adopt a new technology just for the sake of it. 

7. Bridge the gap between product and technology teams

One of the key challenges in driving digital transformation is the disconnect between product and technology teams. Jill Antweiler, VP and Product Development Practice Lead at Modus Create, shares how these teams often operate with differing priorities-product teams push for rapid features and customer enhancements, while technology teams grapple with technical debt and outdated systems.

As Jill explains, bridging the gap between product and technology teams is critical for organizations aiming to modernize their offerings and leverage the full potential of AI. Open communication and shared objectives are essential to aligning both teams.

Gartner reports that collaborative, cross-functional teams are 5.4 times more likely to achieve high digital judgment, demonstrating the importance of fostering empathy and mutual understanding across disciplines. By involving both product and technology teams early in the planning process, organizations can ensure smoother execution and avoid costly misalignment.

8. Demonstrate a commitment to your people

Successful AI-led digital transformation doesn’t solely rely on technology; it depends heavily on leadership that inspires and motivates teams. As Caroline Adams, VP and Digital Operations Practice Lead at Modus Create, explains, being an effective leader during digital transformation means setting a positive example by demonstrating enthusiasm and commitment.

For teams to remain motivated and aligned with strategic goals, Caroline says that leaders need to actively show their investment in the digital transformation process.This includes fostering a culture of adaptability, continuous learning, and collaboration. Digital transformation efforts are 5.8 times more likely to succeed when CEOs communicate a compelling change story, underscoring the importance of leadership involvement.

Leaders who visibly engage with the digital transformation process, celebrate small wins, and empower their teams to take ownership create a lasting impact on organizational culture. If your team sees your excitement for digital transformation, they’re far more likely to embrace the changes required for success.

Successful AI transformation doesn’t solely rely on technology; it depends heavily on leadership that inspires and motivates teams.

Transform AI’s potential into real business outcomes

AI-led digital transformation holds immense promise, but as these industry experts have explained, its success hinges on much more than just adopting the latest technologies. It requires a clear strategic vision, a prioritization of security, and an approach that puts your people and customers first. The journey is complex, but the rewards-ranging from improved customer experiences to streamlined operations-are well worth the investment.

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