Artificial intelligence in 2025 is no longer an emerging trend—it’s a business imperative. According to Hitachi Vantara’s State of Data Infrastructure Global Report 2024, AI adoption is widespread, with 76 percent of organizations rolling out AI for critical or widespread use cases.
AI is booming—and for good reason. In Q3 of 2024 alone, building up AI technologies accounted for up to 20 percent of real GDP growth. And thanks to the rise of GenAI, the technology is more accessible than ever. But accessibility doesn’t automatically equal results. To see a true return on investment, your customers need more than AI tools—they need a solid strategy.
Sheila Rohra, CEO of Hitachi Vantara and a Forbes Councils member recently shared with Forbes some tips to ensure that an organization’s AI journey delivers tangible business outcomes. Here’s a summary of her advice:
1. Be Selective, Not Swept Away
AI has captured global attention, but not every implementation leads to success. The most effective AI strategies begin with focus. Start by identifying a few high-impact use cases where AI can enhance efficiency, streamline decisions, or automate routine tasks.
Don’t default to what’s trendy—prioritize what your business actually needs. And remember, AI strategy isn’t one-and-done. Keep reevaluating, adjusting, and tuning your approach as the technology—and your business—evolves.
Working with a partner that understands your industry and AI’s nuances can also help you avoid missteps and accelerate ROI.
2. Simplify, Scale, and Break Down Silos
AI can be complex—but your approach shouldn’t be. Choose integrated, scalable solutions that combine storage, compute, and AI software in one package. These turnkey offerings can save you time and reduce risk.
But no AI system can succeed without good data. Unfortunately, many enterprises are drowning in “dark data” hidden in isolated silos. Invest in tools for data governance, cataloging, and compliance so you can actually find and use your data to power AI models.
Keep it simple: focus on one or two key use cases, update only the infrastructure you need, and resist the urge to overengineer.
3. Make AI Core to How You Operate
After you’ve nailed a few use cases, expand AI across more workflows. With every success, your team gains expertise and confidence—and AI moves from experiment to essential.
In the next few years, AI will likely become so embedded in business operations that it won’t be a buzzword anymore; it will just be how things work. Think Siri, but for enterprise operations.
The key is to democratize AI—not just within the tech team, but across your entire organization.
4. Prioritize Responsible AI Integration and Data-Driven Decision Making
In another recent article that includes advice from 20 executives on how to maximize AI, Rohra offered her ideas and expertise. She notes that to truly level up AI literacy across your organization, shift the conversation from hype to impact. That means prioritizing responsible AI integration and grounding every move in data-driven decision making.
Don’t just chase the newest tools—choose AI solutions that align with clear business objectives, deliver measurable ROI, and minimize environmental impact. Think before you deploy: a little upfront clarity around outcomes can save serious time and budget downstream. The sweet spot? Innovation that’s efficient, ethical, and sustainable. That’s how you future-proof both your operations and your conscience.
A Marathon, Not a Sprint
Rohra recommends that solution providers and businesses should approach AI as a long game, not a sprint. Stay focused, be practical, and scale with purpose—and your AI investments will pay off in real business impact.
Read the ROI article from Rohra and learn how to level up your AI from her and other executives.
Image Credit: Hitachi Vantara, Getty Images