While the potential of AI-driven archive management is clear, successful implementation requires careful alignment with business objectives. Our survey shows variations in how organisations prioritise archive monetisation, from "critical" to "low", reflecting different business models and digital transformation stages.

Ayushman Saha articulates this fundamental principle: "If an organisation lacks a clear strategy for leveraging their archived information, the investment becomes questionable regardless of how impressive the technology might be." This insight captures the essence of effective technology investment – purpose must drive implementation, not the other way around.

The challenge extends beyond purchasing technology to ensuring adoption. Saha explains, "Many organisations have purchased company-wide AI tool licences, representing significant investments, especially when providing access to thousands of employees. However, we often see only 5-10% becoming regular users. This highlights the importance of having a foundational understanding of how new technology will either improve current operations or support strategic initiatives."

McKinley Muir Hyden shares the Financial Times' approach to technology implementation: "Any new technology must fulfil a genuine commercial or customer need rather than being adopted for its own sake. Second, we need to consider both short-term returns and long-term implications for our business model. Finally, ethical considerations must be central to our decision-making, particularly when working with generative AI."