For those who attended Dreamforce this year, it was clear that the show stealer was artificial intelligence (AI), and the transformative role it will play in how we do business, how we run the machines that run our world, and how we interact with the world around us. Anyone who participated in the keynotes or visited the exhibits in the Campground experienced the power and possibility of AI.
One takeaway from Dreamforce stands out to me: Much still needs to be done on all fronts to turn data into meaningful insights and translate those insights into valuable products and services that customers trust. As Mark Benioff put it in his keynote address, “the AI Trust gap” still needs to be resolved. At this stage of the game, many organizations are able to collect large volumes of data. Let’s use the example of data around critical assets (for example, diagnostic medical equipment or energy generation equipment). Most OEMs and operators of critical assets have figured out how to collect data from these assets. In fact, many are overwhelmed with more data than they know what to do with! The issue is not how to gather data, but rather how to turn that data into valuable outcomes that customers trust.
So, how can organizations begin to create the trust needed to deliver AI-driven outcomes for their customers? Answering these three basic questions can help:
Do you have the right processes in place to turn data into outcomes?
In an asset-centric world, the success of an AI-driven strategy depends on being able to break down organizational silos and allow your best and brightest users and experts to interpret the asset behavior they are capturing with the data. Business leaders need to adopt change management strategies that promote open and collaborative organizational cultures and challenge key stakeholders and experts to work together to turn insights into value-added solutions for customers.
Have you created a shared vision around the outcomes you want to drive with your AI strategy?
Work with your customers to implement AI strategies that are relevant to them. Understand your customer’s priorities: Are they focused on driving uptime, reliability, availability, or maybe greater sustainability from their assets? Can you collaborate with your customers to validate the assumptions driving AI algorithms? Engaging customers upfront in these conversations will help build a relationship of trust that will help you target the right AI initiatives to bring growth and mutual benefit for you and your customers.
Have you engaged your most valuable resource, your asset experts, to help you turn your AI vision into reality?
As important as it is to engage your customers in validating your AI vision, it is just as important to engage your asset experts in executing that vision. Your remote and field technicians understand how your assets behave under operating conditions better than anyone else: They are your eyes and ears on the assets. Your technicians can help you enhance your algorithms with field data and remote monitoring insights. And your technicians are a trusted resource for your customers. No AI strategy or resulting service offering should be considered “validated” without their insights.
“By combining the power of AI with the expertise of our remote and field technicians, we’ve gone from fixing what breaks first to fixing what is most critical.” – A SerivceMax customer on the value of combining AI insights with people insights
The transformative power of AI should not depend on some Orwellian future where equipment and processes run without human intervention, but rather on bringing the best that AI has to offer, combined with the inimitable imagination, ingenuity, and problem-solving skills that people bring to the table. It’s the human element that builds trust in the technology, and it’s the human element that will continue to provide the “spark” that creates smarter, more sustainable, and more relevant products and services.
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