There should be no question by now that artificial intelligence (AI) is poised to change the distribution industry. While there may be arguments around how quickly it will occur or how AI will change workflows, the reality is that AI isn’t coming — it’s already here.
The topic of change came up recently in a Distribution Strategy Group panel discussion with DSG Co-Founder Ian Heller called “AI, Machine Learning and Robotics for Distributors.” The featured panelists included:
- Andrew Creamer, COO of Proton.ai
- Jason Hein, Principal B2B Visionary at Bloomreach
- Graham Smith, Business Development Manager at Esker
What impact will AI have on distribution in the coming years and what will this change mean for companies? Here’s what these industry experts had to say.
Impact of AI on Distribution
Smith said AI is here to stay.
“I was reading an Accenture article recently, which said that 98% of global executives agree that AI foundation models will play an important role in their organizational strategies over the next three to five years,” he said.
Smith is talking about the 2023 Accenture study of generative and other forms of AI and their impact on business. In the coming years, Accenture estimates as much as 50% of all working hours will be supported or augmented by language-based AI.
If you’re unfamiliar with the term, language-based AI is known as natural language processing (NLP), a subset of AI algorithms that enable computers to understand and generate human language. These tools allow intelligent search features on AI-enabled software products. They’re also behind the recent ChatGPT sensation.
Creamer understands these tools better than most—his company incorporates these algorithms into a functional sales platform for distributors. This is just one area where AI will make waves in the distribution space.
“Companies are looking at where the opportunities are—and the risks,” Smith said.
One of the most significant risks in any rollout is user adoption.
Change Management in AI Requires New Partnerships
The first rule for any technology implementation is that a tool is only as effective as we allow it.
According to Heller, the problem with AI is its innovativeness: “Change management was hard enough in the digital era when you could hire people who were experts at digital. Now, it’s the AI era where those experts don’t exist yet in many cases. Or if they do, you can’t afford them. So, this is a unique change management task.”
Creamer agreed:
“From an expertise standpoint, this is a compelling argument for working with a partner. At this point, companies can say, ‘Hey, we have done this for 20 other customers that look exactly like you, same size, same industry, same vertical, etc.”
These companies have seen what’s working and what isn’t from a change management and workflow perspective. These consultative partnerships become more valuable when the software is as sophisticated (and new) as AI.
ERP vs. AI Rollouts— Are They That Different?
But is implementing AI different from a massive rollout of an enterprise resource planning (ERP) platform, for example, or warehouse management software (WMS)? Companies have struggled with change management around technology rollouts for decades.
ERP platforms affect every business area. Change management for these large technology platforms is like what’s needed for AI. What makes these rollouts successes or failures?
McKinsey found that most digital transformation projects (70%) fail primarily because either the stakeholder at the top of the company didn’t believe in the initiative or the end-users on the frontlines failed to embrace these changes.
“I would say that biggest thing that I think is going to keep people from really benefiting from deploying AI is the culture that you’ve built within your organization,” said Hein. “If your senior leadership is still operating from the perspective that outside sales is the only thing that matters, you’ll struggle to get the resources you need to build an effective working relationship across departments and partners.”
“The only thing I would add is just making sure that those resources can be engaged,” Smith said. “A lot of times we talk with companies that want move the project forward and the executive team is engaged. Then suddenly, they realize that they have a six-month roadmap, or they have an ERP upgrade pending. They have resources allocated elsewhere. So, making sure that you get that group involved and ready early is really help helpful in being able to mobilize that project.”
The scope of an AI-based software rollout may require more stakeholder support than rolling out the average software-as-a-service (SaaS) platform because these tools go one step further in supplementing or replacing manual human workflows. Automation in SaaS was step one. An AI-enabled platform can change how a sales rep conducts their business. Some of these platforms enable a revolutionary workflow change that is, in truth, more intense than just rolling out the typical digital product. AI in distribution has the chance to change how we do business. The question is—is distribution ready?
