Conversations about AI will soon involve governance from the very beginning
Companies are facing immense pressure from their board and other stakeholders to incorporate AI. Unfortunately, in the rush to adopt AI, many organizations have neglected perhaps the most important element of AI adoption: data governance.
The process of managing and governing the data underlying an AI system is complex. If leaders don’t understand the importance of high-quality data, AI projects will face setbacks and even failure. And for regulated industries, like pharmaceuticals and medical devices, where adherence to strict compliance standards is mandatory, this challenge is amplified.
Just imagine the fallout that could occur if an AI-powered healthcare platform collected sensitive genetic information from a client, only for that information to get leaked to bad actors. That patient could then be exposed to malicious health-related scams. Simply put, many leaders need to refocus on data governance before even considering AI.
By integrating governance protocols into AI workflows, companies can mitigate risks related to data oversight and maintain compliance. Such built-in AI capabilities will prevent organizations from being blindsided by regulatory and data security hurdles, enabling them to pursue innovation more confidently. We’ll see many organizations turn to these options in 2025 as they seek to reiterate their current AI solutions.
AI will build resilience in our global supply chain
Since the beginning of the COVID-19 pandemic, several geopolitical events have exposed vulnerabilities in our global supply chain (the Suez Canal blockage and ongoing conflicts in Ukraine and the Middle East, to name a few).
In response to this fragility, many companies will leverage AI to create more resilient supply networks. AI-driven tools will monitor events and interpret data in real time, alerting organizations to potential disruptions, such as unexpected production halts and even political unrest. Industries relying on globally sourced components, particularly those dealing with microelectronics and specialized manufacturing parts, will benefit the most from this trend.
Furthermore, the predictive capabilities of AI will extend to strategic planning phases, allowing for early identification of supply chain risks and the development of contingency strategies, such as diversifying sourcing locations. This proactive approach will become a competitive advantage, ensuring continuity even in turbulent times.
Everyday use cases for AI will continue to revolutionize business
Employees have started integrating AI use cases into their everyday lives, from answering tough research questions with ChatGPT to summarizing long meetings with AI-generated transcripts and notes.
These common use cases will continue to free up employee time, enabling people to focus on higher-value activities that require strategic thinking, creativity and decision-making. However, the proliferation of AI will also deeply impact the success of third-party solution implementation and vendor relationships. AI can expedite the due diligence process significantly, enabling organizations to rapidly understand solutions and their success rates.
This will lead to deeper and more successful relationships with many third-party vendors in 2025.
Low-code solutions will prove crucial for successfully leveraging AI
The growth of low-code and no-code platforms has empowered employees, termed “citizen developers,” to create solutions tailored to their roles without involving traditional IT teams. This shift will democratize tech development and increase agility and innovation within organizations.
However, to ensure that low- and no-code solutions remain compliant and secure, organizations will need to partner with a knowledgeable third party that can step them through the process of tool adoption. Integrating AI and third-party vendors as “watchdogs” can help monitor and flag deviations, supporting IT governance while fostering a controlled environment for employee-led innovation.