Each year Algorithmia produce an Enterprise trends report about AI and Machine Learning. The comprehensive report is based on 400 company leaders with revenue over $100m or more.

Key findings #1
Organisations are increasing AI/ML budgets, staff and cases. The pandemic seems to have fuelled more urgency, with 83% of org increasing their budgets for AI/ML. The average amount of data scientists has risen to 76%.

Key findings #2
56% of organisations rank governance, security and audibility issues as a concern. 67% of orgs report needing to comply with multiple regulations when using AI/ML.

Key findings #3
Despite increased investment and staff, organisations spend more time and resources on model deployment than before. Most projects took a month longer than I thought. Most orgs are spending more money but need to improve efficiency.

Key findings #4
Algorithmia has also learnt that most orgs see improvement with 3^rd party solutions to manage their AI/ML operations (MLOps), allowing them to spend up to 21% less on infrastructure.

2021 report, click here

In summary
It is encouraging to see that most business leaders were more concerned about improving their AI/ML. There is no question that the pandemic has had a significant effect on every industry. It has fuelled further investment and interest in AI/ML.

Also – The top 10 trends include

1. Priority and budgets for AI/ML are increasing significantly year-on-year.
2. Organizations are expanding into a broader range of AI/ML use cases, focusing on process automation and customer experience.
3. Most organisations have more than 25 models in production, but there’s a gap between AI/ML “haves” and “have-nots”.
4. Governance is the top challenge for AI/ML deployment, with more than half of all organisations ranking it as a concern.
5. The second greatest AI/ML challenge is technology integration and compatibility, with 49% of organisations ranking it as a concern.
6. Successful AI/ML initiatives require organisational alignment across multiple decision-makers and business functions.
7. Organizational alignment is the most significant gap in achieving AI/ML maturity.
8. The time required to deploy a model is increasing, with 64% of all organisations taking a month or longer.
9. 38% of organisations spend more than 50% of their data scientists’ time on deployment, which only worsens with scale.
10. Organizations that use a third-party machine learning operations solution save money and spend less time on model deployment than those that build their solution.

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I invest many hours researching the latest AI, technology, and business trends for all my clients. The knowledge is refined, distilled, and combined with many other forms of analysis and expertise to give the best advice possible. 

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