Start with Business Goals to Maximize AI Success

Jen Anaya, SVP, Global Marketing, Ingram Micro

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As the excitement about AI and generative AI (gen AI) continues to build, so does the urgency for businesses to harness its potential or risk becoming irrelevant.

 

Unlike what you might have read in headlines, AI adoption isn’t an all-or-nothing game. It’s a long game requiring business leaders to start small but think big.

 

If you are tasked with using AI to better the business, ask yourself: how can we apply AI to our existing business strategy and fundamentals? Whether you’re a startup or an enterprise, using AI to establish and automate clear processes and ROI metrics is a great starting point.

 

Or what about using AI to further educate, iterate and learn as a team and with your customers? Sharing an experience can drive tremendous success and growth together, now and in the future. 

 

Adopting AI doesn’t have to be a moment of reinvention. It’s about refreshing what’s relevant today, and what can be even more so tomorrow. Think about how AI can help you reimagine what you or your teams are tasked with every day, or how you could create a better experience for your customers. Here are a few suggestions to get you thinking differently about how to apply AI inside and outside of your organization.

 

Begin the journey with clear outcomes

 

The recent Nobel Prize awarded to Drs John J Hopfield and Geoffrey E Hinton for pioneering machine learning highlights AI’s power to mimic human thinking – a cornerstone of today’s AI-driven innovations. From transforming customer service to reshaping application development, AI offers immense potential in personalised engagement at scale. However, the path to meaningful AI results starts with asking, what specific business value do we want to uncover and can AI deliver? And don’t forget to measure with the question, and by when?

 

When companies set intentional, outcome-based goals, AI initiatives become more straightforward to plan, implement and measure. At Ingram Micro, for instance, we built our Ingram Micro Xvantage platform to unify and maximise the value of data across global databases. By clearly defining our goal – to deliver actionable business insights in real time to customers – we shaped an AI solution that transformed our data into a competitive advantage for our customers and us.

 

Agile, incremental integration is key

 

Agility, a tried-and-true software development approach, is essential for successful AI deployment. Companies that take an agile, incremental approach to AI avoid the risks of sweeping changes by learning and adapting at each stage. Small, controlled steps allow teams to fail fast – learning from each attempt and building a more robust solution through continuous iteration.

 

By integrating AI incrementally, businesses can fine-tune their strategies, leveraging small successes and valuable insights. This process mitigates risks, avoids setbacks, and promotes a sustainable path to AI adoption. As Ingram Micro’s CDO Sanjib Sahoo says, there is no stop sign for digital transformation, and the same is true for AI. It’s a journey, not a single destination.  

 

Measure ROI from multiple perspectives

 

Defining measurable ROI for AI investments is critical and challenging. Your CFO, for example, may focus on direct financial returns, while development teams value efficiency gains and product quality. Consider the impact across the organisation: employee productivity, customer satisfaction, time to market and more.

Being forward-thinking with others in your organisation and within your customer base will save you time in launching AI-enhanced customer experiences. It will also lend competitive insights gained from AI-powered analytics that can translate into measurable, strategic value.

 

To that end, to calculate ROI effectively, make sure to link your AI goals to the specific groups they benefit and the metrics they stand to improve. This clarity helps justify investments and manage expectations across departments, ensuring alignment on what success looks like for each team and making it more personalised.

 

Foster collaboration and trust across teams

 

AI projects are most successful when they are embraced across the organisation. Establish clear communication channels to keep stakeholders – from developers to sales teams – updated on project progress, challenges and timelines. Real-time transparency fosters a collective belief in AI’s potential, building trust and driving commitment to achieving project goals.

 

When teams share a unified vision, AI development benefits from broader input, smoother adoption and a greater sense of ownership. AI becomes an initiative and a shared opportunity for innovation and growth.

 

Avoid the hype – stay focused on fundamentals

 

While gen AI’s appeal is undeniable, focusing on the fundamentals is critical. A Stanford University study of Fortune 500 executives highlighted inconsistent outcomes and costly setbacks among AI initiatives, often due to failure to align AI capabilities with real business needs. By prioritising core principles – defining clear outcomes, knowing the end user, practicing agile development and setting measurable ROI – businesses can avoid many common pitfalls.

 

In today’s fast-moving landscape, companies that stay rooted in the basics will see the best AI outcomes. By following these fundamentals, you are better positioned to use AI as a powerful driver of value and a key differentiator in the market for your company and your customers.