Artificial intelligence has been a longstanding presence, but its current explosion onto the scene is undeniable. As companies increasingly recognize the vast potential of Generative AI, they’re swiftly accelerating existing projects and launching new initiatives across all areas of the business —from supply chain to HR, sales, and marketing.
Yet, leaders are faced with the task of managing it all. The conventional wisdom might suggest centralizing control under a seasoned executive, but that’s not necessarily the right approach.
History has shown that when new technologies emerge—be it the metaverse, blockchain, or now AI—companies often rush to appoint a designated senior leader, a “czar” of sorts, assuming it will solve their adoption challenges. However, this reaction is frequently a big mistake.
Typically, the process usually starts with the board hearing about the latest tech buzz, followed by teams pitching optimistic yet conflicting use cases to leadership. Fueled by excitement but lacking clear direction, the board assigns responsibility to an individual who often finds themselves overwhelmed and underprepared.
Unfortunately, this strategy rarely yields the desired results. After years of grappling with the technology and minimal progress to show for it, the appointed leader often exits the company, leaving behind a trail of disappointment.
However, this outcome shouldn’t come as a surprise. These failed leaders often lack a deep understanding of how the company operates on the frontlines, where ideas are translated into action.
So, what should companies do instead?
Lead from the Frontlines
In developing applied technologies like AI, leaders must identify opportunities within workflows. In other words, to find a use for a new piece of tech, you need to understand how stuff gets done. Czars rarely figure that out, because they are sitting too far away from the supply line of information where the work happens.
There’s a better way: instead of decisions coming down the chain from above, leaders should let innovation happen on the frontline and support it with a center of excellence that supplies platforms, data engineering, and governance. Instead of hand-picking an expert leader, companies should give teams ownership of the process. Importantly, this structure lets you bring operational expertise to bear in applying technology to your business, responsibly and at scale and speed.
Sharpen Performance
Our progress is improving. Thanks to our AI search bot, our answer accuracy rate now rivals that of our human counterparts, but we’re setting our sights on achieving a staggering 99% accuracy. This improvement is a daily effort, but our success lies in enhancing our net promoter scores, which is our goal this year.
Likewise, in sales, we’ve initiated the deployment of an AI tool to forecast customer preferences and proactively offer tailored options. By capturing a wealth of data points, we generate over 100 predictions that enhance customer experiences significantly—whether it’s suggesting optimal network and content choices aligned with their interests or presenting them with personalized promotions based on their tenure. Identifying and meeting customer needs in advance enables us to resolve queries swiftly, often on the initial interaction.
This proactive approach has already promoted our sales conversion rate by more than 6%, encompassing everything from fresh subscriber acquisitions to enriching existing plans with exclusive perks and upgrades. AI empowers humans to excel in their areas of expertise, while machines handle tasks suited to their capabilities.
To underscore this synergy, we’ve empowered our frontline teams to steer the utilization of AI, aiming to streamline processes and lighten cognitive loads, all while delivering exceptional customer service centered on human interaction, empathy, and surpassing expectations. There’s no autocracy in customer interactions; instead, decisions are made at the frontline by using the expertise of our team members. Performance insights flow upward, facilitating organization-wide assessment and refinement. In our pursuit of optimal outcomes, we’ve decentralized decision-making, aiming to harness the collective wisdom of the enterprise.
Artificial intelligence reminds me of the internet internet boom of the early 2000s. Back then, everyone was eager to establish their dotcom presence, but not all succeeded.
It took more than just adding a .com to your name or appointing an internet-savvy executive. Similarly, in today’s landscape, every company is eager to incorporate AI, but sustained success requires more than merely assigning a leader to oversee it.
The triumph or failure of AI initiatives isn’t solely the responsibility of a single individual; rather, it rests with an empowered group of stakeholders who actively monitor results, customer engagement, and feedback. While it’s crucial for organizations to have a clear vision for AI, history demonstrates that those who leverage the insights and talents of their frontline staff gain a competitive edge. This principle holds true for AI implementation today.
For more information, please contact:
Karlheinz ZUERL – CEO of GTEC (German Technology & Engineering Cooperation)
E-Mail: [email protected]
Mobile: + 86 13482438080
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