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Blog June 14, 2024

4 Takeaways from 2024’s Applied AI for Distributors Conference

CapTech has been focused on solving our distribution clients’ most pressing business challenges through the application of data, technology, and AI solutions for decades. Our recent attendance at the Applied AI for Distributors conference in Chicago was inspiring, as we met with many distribution leaders who were ready to embrace, or are already actively embracing, AI and its potential to transform their business. Being a part of the many discussions, as well as presenting CapTech’s framework for accelerating AI initiatives forward, was invigorating. Our framework resonated with many attendees, and it sparked some great conversations.

As we reflected on the conference, four key takeaways emerged.

1. The Time is Now for AI Adoption

June’s conference wasn’t just informative, it was a call to action. Data overwhelmingly shows that early AI adoption is key to gaining a competitive advantage and there was one consistent message throughout the conference: start now.

According to Distribution Strategy Group, the event’s organizer, early adopters could see a staggering 122% increase in revenue, while those who wait risk a 23% loss. While specific figures might vary across industries, it’s clear that companies effectively integrating AI into their operations are often rewarded with increased efficiency and revenue growth.

2. Every Distributor Can Start, or Accelerate, Their AI Journey

No matter the stage of their AI journey, there was one consistent theme amongst the industry leaders we met with: it’s all about making progress. By evaluating their current AI maturity through an assessment, developing a roadmap, and taking the logical next step, distributors at any stage can propel their AI initiatives forward. Here’s how:

  • Distributors who haven’t begun implementing AI solutions should find an initiation point. And while it can be daunting – we encourage clients to start small. Look to implement an AI pilot that is tied to true business value, delivers a quick win for the business or builds momentum. Examples might include faster customer service resolution through chatbots or autonomous virtual agents, improved demand forecasting and inventory management through predictive analytics, and dynamic pricing based on season, weather, and traffic.
  • Distributors who have already launched AI initiatives should measure their performance to refine and expand capabilities through continuous improvement and thoughtful scaling.
  • Distributors well into their AI journey must continue to optimize by sharpening their business and data strategies and processes, continually refining solutions, and staying ahead of the curve as these technologies rapidly evolve.

3. IT and Business Leaders Must Collaborate

Deploying AI for AI’s sake is a recipe for failure, and it was validating to hear so many presenters aligned to this sentiment. A successful AI deployment requires tight alignment between business needs and IT operations, and presenters were quick to point out that organizations can no longer treat AI as an experiment separate from their core company objectives. Instead, IT teams, business unit leaders and company executives must consider AI an additional tool that is central to solving to real business challenges, driving efficiency, and opening up new revenue opportunities. Bridging the IT-business divide is critical for ensuring AI investments translate into measurable results. Companies who get this right are on the leading edge.

4. Rapid AI Evolution Can Be Challenging

Today, AI, and now generative AI, are household terms. While the conference focused heavily on the various AI opportunities that an organization can embrace, it's also a good time to examine the associated challenges. Chief among the challenges is the pace of AI evolution. As “Martec’s Law” illustrates, while technology changes fast, organizations may not.

Companies must evolve in lockstep with AI's rapid-fire advancements, which oftentimes requires a culture-shift towards experimentation and proactive learning, and being okay with the notion of failing fast. For those able to view change as an opportunity rather than a threat, the AI revolution presents immense potential for creating long-term competitive advantages.