There’s also the technical work business leaders need to consider when investing in AI and, given its complexities, organizations are leaning on vendors to assist with its execution. AI isn’t one big destination feature; very few organizations will directly integrate with models on their own or have their teams chat directly with them. AI is a substrate that will become embedded throughout your stack, from chips, to databases, to application software.
Think of it not as a new type of tool, but a stronger building material for your existing tools. For vendors, there’s a responsibility to deploy AI solutions as an add-on to existing workflows, minimizing hong kong mobile database friction and prioritizing intuitive design. And for functional leaders like CMOs and CTOs, there’s a responsibility to observe how their teams leverage AI and share that feedback with their vendor partners for future iteration. We’re building the future of work together.
The emergence of AI has already impacted the way some organizations work and how leaders are thinking of their future technology investments. From increasing productivity to simplifying data analysis, AI has shown early proof points of its potential.
But there are untapped opportunities we’ve yet to realize because AI, and the tooling that embeds it, needs time to mature. We still have to answer questions around safety and ethics, and to establish rules of engagement for how AI should be leveraged and where. There’s also the internal change management that needs to occur before executives even consider AI implementation. All of this is dynamic, and will evolve over time.