Many enterprise AI efforts stall because leaders buy tools before diagnosing real operational gaps, aligning teams, or preparing systems to work together.
Joe Ligé, Co-Founder and Chief Business Officer of Adte, says AI succeeds when leaders start with internal diagnosis, prioritize speed and efficiency, and build strong human oversight.
Sustainable results come from disciplined rollout, continuous feedback, cross-system communication, and a clear decision on risk appetite and timing.
As the enterprise conversation around artificial intelligence has moved from hype to execution, many leaders are finding that initial efforts have failed to deliver real value. Successful AI adoption is a process, not a product. It's an ongoing commitment that typically begins with an internal diagnosis long before the selection of any tool. Now, leaders are scrambling to establish processes that allow for more successful AI adoption before being left behind.
Joe Ligé is the Co-Founder and Chief Business Officer of the video advertising platform Adte and the Founder and CEO of the cultural intelligence firm Culture Hive Media Group. He has a track record of making new AI-based technology deliver measurable results, including the development of Culture Hive's CulturaGPT and AI-powered Hexagon DSP.
Ligé dispels the misconception that AI can be a quick, one-time solution. "With AI, it’s never set it and forget it," he says. "You’re constantly testing, adapting, and investing. It's like upgrading to the next iPhone. If you stop, your system stops being as effective."
Diagnosis first: Leaders should first diagnose the specific, practical problems inside their own organizations, Ligé says, focusing on speed and efficiency as the primary metrics for success. "You've really got to start with: what are my areas in my business that I need help with? Where can I save time? Where can I save energy? Money is a byproduct of those things." His strategy calls for a foundational commitment to human oversight. He explains that AI, for all its power as a suggester, often lacks the nuanced context to handle emotion or human relationships.
Once the philosophy is set, a roadmap needs to navigate the messy reality of hands-on deployment. "The other part of that is training the AI," says Ligé. "Making sure that it understands how to read your data, what that data means to you." A successful technical plan must then navigate two great barriers: people and systems, along with how systems communicate with one another.
Change management: "Change management is probably the most important aspect because you need a lot of feedback," says Ligé. "When you're rolling out any AI solution, you need that human feedback on whether it's helping or not." The second barrier is systemic. "You can have a lot of inputs, but AI operates in silos until it can talk to each other across," he says. "If the other system you're trying to talk to doesn't understand what that data is, then it's not going to work together. There needs to be an underlying communication layer so that data can be passed and understood across boundaries."
Watched by the machine: "I saw an example where a company used AI to score sellers on keyword mentions, but it completely ignored the context of the conversation. It made sellers afraid to build rapport because they felt they were being watched by the machine. That kind of system doesn't help them become better sellers; it just causes angst and leads to turnover," Ligé recalls.
Lost in translation: "When your internal systems can’t communicate, it's like trying to build a house with carpenters who all speak different languages. They all have the skills, but orchestration is incredibly difficult if they can't agree on basic terminology. That shared language has to be established first."
Ligé points out that all of this is framed by adoption and timing. Depending on when enterprise leaders choose to adopt a new AI tool or system, a simple technology upgrade can turn into a high-stakes bet on market timing. "Ultimately, every leader must decide whether to be a first mover or a fast follower. Are you a Samsung or an Apple? It's a gamble. Sometimes you bet on a hit, and it fails spectacularly. Your organization's appetite for that risk is what should determine how far you go."
