Unclear strategies are thwarting AI at traditional companies

Key Takeaways:

– Traditional organizations have high hopes for AI but face strategic shortcomings that limit their ambitions.
– Silo AI, a startup based in Finland, conducted a report analyzing various traditional businesses and organizations.
– Despite their age, all surveyed companies are engaging with AI to some extent.
– However, almost half of these companies feel neutral about the results of their AI projects.
– The main challenges identified are unclear strategies and absent executives responsible for data and AI management.
– Most projects are managed locally, creating a fragmented landscape with unstructured data management and unclear governance.
– Silo AI advises appointing a C-level representative to incorporate AI into the organization’s strategy and align initiatives with specific business objectives.
– Specific measures suggested by Silo AI include creating frameworks to assess the ROI of AI projects and establishing an AI center of excellence.
– Only a quarter of respondents already have ROI assessment frameworks in place, but organizations happy with their AI initiatives are more likely to have developed these structures.
– The holistic approach of establishing an AI center of excellence enables organizations to extract maximum value from their AI investments.
– Deploying AI at the core of products, services, or processes offers the greatest potential for value creation but requires a long-term perspective and significant efforts.

The Next Web:

Traditional organisations have high hopes for AI, but strategic shortcomings are severely restricting their ambitions.

That’s according to a new report from Silo AI, a startup based in Finland. The company recently earned headlines for building a large model (LLM) with multilingual capabilities but primarily focuses on bringing AI into established businesses. That gives it a window into mainstream adoption of the tech. The new research paints a more detailed picture.

The report analysed various traditional businesses and organisations. Silo surveyed companies from assorted industries, from manufacturing and construction to financial services and the public sector. Despite a median age of 87, all of them were engaging with artificial intelligence at some level.

Nearly 70% have experiments or projects in development, while 86% expect their projects to progress into production within the next 12 months. Almost two-thirds (65%) also have prior AI projects that have already progressed into production. 

Their efforts, however, aren’t always successful. Almost half of them feel at best neutral about the results.

Digging into the data, Silo discovered that unclear strategies and absent executives are holding companies back. Most of the respondents don’t have a C-level representative who’s responsible for data and AI management, and the majority of projects are managed locally in each business unit.

This fractured landscape creates several problems.

“One risk is that data management is unstructured and governance unclear,” Peter Sarlin, the CEO and co-founder of Silo AI, told TNW.

“Another risk is that investments in AI and the integration of AI are relegated to different siloes and fragmented across an organisation, while research and development is a largely centralised endeavour.”

To mitigate these risks, Silo advises making someone in the C-suite responsible for incorporating AI into the organisation’s strategy. All the initiatives should also clearly align with specific business objectives.