Global technology consultancies all have an AI strategy. But without proper governance, process and supporting tooling, AI projects will underperform.

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AI is a highly strategic focus for global technology consultancies across geographies and industries as clients move to unlock ROI in their data and bring Machine Learning technologies to their business. Typically, projects start with smaller PoCs, evolving to pilot projects before final rollout at scale when and where client value is proven.

Many PoC projects begin with a high focus on data science but increasingly shift to system integration and data engineering as they progress. Consultancies tend to have both strong data science and systems integration practice, but sometimes face challenges in bridging the two as PoCs move to full rollout. The result: a loss of project momentum and missed revenue opportunities.

Key AI challenges

  • Accurately reproducing results between team members due to the high number and variation of factors that contribute to model performance.
  • Collaborating and comparing models and results, particularly to get a comprehensive view of the combination of training factors that contributed to performance differences.
  • Lost client opportunities due to wasted resources, missed milestones, team frustration and the risk of suboptimal model performance during the pilot and PoC process.
How can Dotscience help?

Dotscience can provide a more managed and collaborative work environment for data scientists which can help to reduce staff churn and mitigate its impact when it does happen. Additionally, it provides a more controlled and faster workflow which supports an acceleration in the AI strategy.