“There is significant potential in AI, but the technology itself is only useful if applied to the right business use case,” said Sanjib Sahoo, executive vice president and chief digital officer at Ingram Micro.
As AI penetrates deeper and deeper into business operations, its potential to transform the company operations remain vast. However, Ingram Micro’s Sanjib Sahoo said the key to success lies in aligning AI with clear business objectives and applying it to solve real-world challenges.
While the future of enterprise AI is rife with opportunity, businesses must approach its adoption with a strategic and thoughtful mindset to ensure long-term success.
“Proactive adoption of AI starts with the right mindset: people, mindset and innovation,” said Sahoo, executive vice president and chief digital officer of the Irvine-based IT distributor , in California, at CRN. “It is crucial to focus on customer needs and business goals first. Then use AI as a tool to achieve these goals.
Two years after launching its transformative Xvantage platform, Ingram takes the next step in its plan to deliver a highly personalized experience for solution providers with Ingram Micro Ultra. The offering aims to transform its interactions with solution providers by integrating cutting-edge AI and a tailor-made rewards system.
“With Ultra, we are moving from a transaction-based model to an interaction model,” Sahoo said. “The program is designed to reward partners not only for their transactions but also for their engagement and loyalty. By leveraging Ingram Micro’s 40 years of data and solutions capabilities, we can deliver a more comprehensive and personalized experience.
At Ingram Micro’s One conference in Washington, DC last week, the distributor also announced Xvantage Enable and Xvantage Assist, new tracks that will further educate, train and inform channel partners on opportunities and challenges related to AI. Both tracks will also help accelerate AI adoption among channel partners and their customers by enabling them to better navigate an evolving technology landscape with greater confidence. “Support is a question of capacity. Enable is about go-to-market strategies,” Sahoo said. “Together they create a powerful ecosystem for our partners. »
Find out what else Sahoo had to say about AI, business maturity and how building a strong AI foundation can help organizations with their AI strategy.
How do you define the role of AI in business today?
AI holds significant potential, but the technology itself is only useful if applied to the right business use case. The true power of AI lies in how you tailor its capabilities to business needs. It’s not about having an AI strategy in isolation, it’s about integrating AI into your existing business strategy. That’s when you start generating real value. There’s a lot of talk about what AI can do, but we need to focus on what it actually does for businesses today.
Can you explain the difference between having an AI strategy and integrating AI into a business strategy.
Having an AI strategy is more about technical exploration, such as creating a center of excellence, hiring data scientists, and testing large language models or machine learning algorithms. But business strategy is about solving real business problems. For example, if you are looking to improve customer experience or operational efficiency, you use AI to solve those specific problems. The business strategy remains the same: you simply leverage technology to solve problems. This is the key distinction.
What do you think is the biggest mistake businesses make when trying to adopt AI?
The biggest mistake is trying to go too far, too fast and focusing too much on the technology itself. AI adoption should start small. Think big, but start with one or two use cases. The key is to make sure your operations team and your data teams are aligned, because AI and operations need to work hand in hand. We talk about “AI operations,” where operations teams are closely integrated with data and technology teams to solve real business challenges.
Why is business maturity important before embarking on AI adoption?
Business maturity is crucial because it lays the foundation for AI adoption. If your data is messy or you have outdated systems that haven’t been streamlined, you’ll spend more time cleaning data than applying AI. The maturity of your company also impacts your alignment within teams, your ability to attract the right talent, and your overall willingness to grow. If you’re not ready, you risk investing time and resources into something that won’t pay off.
What are the signs that a company is ready to integrate AI into its operations?
A key sign occurs when a company begins to focus on business outcomes and use data to achieve those outcomes. For example, if you’re using AI to improve customer service, look at key performance indicators (KPIs). Are your customer satisfaction scores improving? Are the number of support tickets decreasing? If you see positive results, that’s a sign that you’re using AI effectively. But remember that AI will never be perfect and so the goal should be to continually demonstrate incremental improvements.
How can businesses identify the right use cases for AI?
It’s all about pairing. First, identify the most complex business problems you need to solve. Next, evaluate the capabilities of different AI technologies to determine which ones can solve these problems. Start with a small proof of concept, measure the results and refine your approach. The goal is to identify areas where AI will provide the most value and build from there.
In your keynote, you mentioned the importance of the three S’s: speed, scale and service. How can companies integrate them into their AI strategy?
AI can improve speed, scalability and service in different areas of a business. Speed could mean improving the speed of decision-making or transaction processing, while scale could be about expanding into new markets or customer segments. Service is about improving the customer experience. The key is to tailor AI capabilities to these specific use cases and start with a few targeted areas where AI can have the most immediate impact.
With legacy systems and siled data, how can businesses create a strong database to support AI initiatives?
Building a strong database starts with streamlining data. You need to evaluate your systems, clean your data, and eliminate silos to ensure data is accessible and usable. We built a proprietary data mesh that aggregates data from different sources. Once you have a solid database, start with smaller, manageable data stores focused on specific business areas, like sales or operations, and address use cases from there. Don’t try to fix everything at once.
How can business leaders encourage proactive adoption of AI within their company?
Proactive AI adoption starts with the right mindset: people, mindset, and innovation. It is crucial to focus on customer needs and business goals first. Then use AI as a tool to achieve these goals. Leaders must create a culture that encourages experimentation, in which failure is viewed as a learning opportunity. It is also important to define clear indicators of success. AI is not about creating fancy algorithms, but about achieving measurable business results.
Looking ahead, what do you see as the biggest opportunity for AI in business over the next three to five years?
The biggest opportunity lies in creating more integrated and seamless experiences across value chains. AI will enable businesses to focus on their core value propositions while integrating with other ecosystems, thereby optimizing cost structures and improving efficiency. AI will drive innovation not only through algorithms, but also by helping businesses rethink the way they operate and deliver value to customers.
