Agur Jõgi, CTO of Pipedrive and expert in scaling technology and organizations. Experienced as an innovator, founder and C-level manager.
Within enterprises, AI adoption has reached a phase where leaders are reviewing early investments and integrations. They are looking to measure and build on early success. By now, colleagues should be comfortable using AI to assist people and for process efficiency to achieve higher quality outcomes with less effort.
This means that the organization must look not only at the hard figures of the P&L but also at the impact of new technologies and processes on its teams and talent. As with every evolution (and revolution), the shine wears off new tools, and people find their own rhythm in using them. Putting it bluntly, without the right skills and culture in place, leaders won’t maximize the return on their AI investments. Culture always impacts how tech is used in practice.
Take the pulse—regular feedback is key.
Let’s assume that by now, organizational leaders have done the following over the past couple of years: First, they have developed a clear and sound strategy to thread the needle between their AI investments and their impact on business objectives. Second, their adoption of AI technologies aligns with business goals, and investments have been made either in safe pilot schemes, ready for a wider roll-out if successful, or projects that were transformational and in line with business goals from the start. Hopefully, congratulations are in order.
So, what’s next? It’s time to go beyond the finances and numbers and check in on users and their expectations. Usage metrics don’t account for willing engagement versus grudging use. Knowing the difference can supercharge better working experiences and stronger business outcomes.
So, review the impact of new tools and processes on your people. Are they being used as expected? How do they feel about adoption? Are they using them as intended, with data privacy and security, or are they using workarounds to make life easy at the expense of robust policy? Ask probing questions from a spirit of honest inquiry.
Handle changing stakeholders and review processes.
Regulators are very interested in how AI capabilities and implementation are growing. In the U.S., an executive order requires safe, secure and trustworthy AI, and there is a blueprint for an AI Bill of Rights. There’s also a U.K. Artificial Intelligence (Regulation) Bill in the early stages of legislative crafting that, among other provisions, may create a U.K. “AI Authority” and accredit independent AI auditors.
The EU was a very fast mover, creating regulations that will come into full force in 2026. Some critical safety aspects will apply to organizations sooner, such as a ban on AI systems potentially offering “unacceptable risks.”
International businesses face decisions around meeting the most stringent regulations as a baseline for global offerings or whether regional customization and geo-targeted features—and the extra work to separate those—are worth it.
Planning, documentation and communication—again—will be key as the interaction of regulation, company policy, applications and underlying infrastructure become a complex patchwork of reciprocity. Any policies and processes that don’t flex will lead to the outcomes veteran leaders forecast: Workarounds, unsafe practices and noncompliance that, even when well-intentioned, can lead to ever more levels of business risk.
Don’t neglect skills and training.
What’s better than one person with some kind of AI copilot? A highly skilled expert who knows their craft inside and out, with an AI copilot. Tech leaders must become champions of skills and training for every department that relies on any kind of AI support to augment and support colleagues. If users don’t have high levels of expertise, AI won’t help them understand if the outcomes are fit for purpose.
Tech leaders must keep in mind that technology and training budgets must be linked if technology is to be used for full business advantage. Where new technologies go, training must follow. When new people come into the business, they will need to understand the business first and specialist technology second. At every level, critical thinking and domain expertise are essential for well-rounded employees to make the most of the tools at their disposal.
Success can be found through technology plus feedback, processes and skills.
AI embedded in solutions like CRM, accounting or HR software is already removing toil and drudgery from users, or supercharging already skilled experts to achieve higher results. Tech leaders must cooperate and think beyond their strict area of responsibility if they want to ensure that the right tools are made use of in the most impactful ways.
It’s up to tech leaders to become as central to the business as AI promises to be for its users over the coming decade.
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