Building a Strategy of AI for Big Data Success: Lessons from Strategic Scalers

Research from Accenture identifies three distinct groups of companies in their AI journey:

Proof of Concept Factory (80-85% of companies)

Strategically Scaling (15-20%)

Industrialized for Growth (less than 5%)

The "Strategic Scalers" who successfully implement AI at scale reveal three critical success factors:

1. Drive "Intentional" AI

Strategic Scalers pilot and successfully scale more initiatives than their counterparts, at a rate of nearly 2:1, yet spend less overall. They're 65% more likely to report a timeline of one to two years to move from pilot to scale, setting realistic expectations. Nearly 71% have a clearly-defined strategy and operating model for scaling AI, compared to only half of companies in the proof-of-concept stage.

2. Tune out data noise

While facing the same data volume challenges as everyone else, Strategic Scalers focus on business-critical data and are better at structuring and managing it. They're more likely to work with larger, more accurate data sets (61% versus 38%) and to integrate both internal and external data (67% versus 56%).

3. Treat AI as a team sport

A full 92% of Strategic Scalers leverage multidisciplinary teams headed by Chief AI, Data or Analytics Officers and comprised of various specialists. These teams, embedded across the organization, enable faster culture and behavior changes than the lone champion approach used by companies still in proof-of-concept stages.

👉 Read more in the article "Leveraging AI and Big Data to Address Business Challenges"

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