71 step is deciding how to determine the relevance of data for AI processing, evaluating the potential value of different data types alongside the legal and ethical considerations of using them. Companies should also assess the ability of their current IT infrastructure to support the content strategy and governance requirements they’ve developed. It is essential to ensure that systems and integrations can facilitate connectivity, confidentiality and curation. When evaluating generative AI solutions, consider factors such as vendor trustworthiness, pricing models and overall cost-benefit analysis. It’s important to choose solutions that integrate well with existing systems and can scale to meet future needs. The business should then take action to assess the current level of automation in their content processes and identify opportunities for expansion. The goal should be to progress from basic automation focused on consistency and compliance to more advanced apps that support decision-making and provide realtime insights. Implementing generative AI solutions often involves reimagining existing processes entirely, and organisations should look for opportunities to transform how work is done and how value is created. The final step is to evaluate how well current content capabilities support end users across different functions and industries. Organisations must consider the varying needs of different user groups and ensure that AI enhances, rather than complicates, their work processes. Assessing the company’s change management capabilities and end users’ readiness to adopt new tools is equally important, as successful implementation often requires significant changes in work practices and mindsets. Businesses should invest in training programmes, create champions within different departments and develop a communication strategy to build enthusiasm and address concerns about AI adoption. Businesses can position themselves to reap the full benefits of AI by following this framework and addressing the foundational elements of information management. The journey to effective AI implementation may be challenging, but the potential rewards – including enhanced productivity, improved decision-making and unlocked innovation – make it a worthwhile endeavour for forwardthinking leaders across all industries. As we move further into the era of AI-augmented information management, the companies that navigate this transformation successfully will be well-positioned to thrive in an increasingly data-driven business landscape. Ville Somppi is senior vice president of industry solutions at M-Files Photo: AdobeStock/ BGStock72 Valuable knowledge can be hard to locate within large organisations
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