Accenture: How to succeed at scaling AI investments
Strategic scalers achieve nearly triple the return from artificial intelligence (AI) investments than companies in the proof of concept stage, reveals a global study from Accenture.
According to the survey of 1,500 C-suite executives across 16 industries - generating between US$1 to US$30 billion a year - it was found that size is not a factor to success – but 76% of executives are struggling to scale AI across their organisations.
“When we grouped the surveyed companies by size, we found no significant differences in scaling success rate or return on AI investments. So, size is not a factor. It’s all about instilling the right AI capabilities and mindset in the organisation,” reveals the Accenture study.
A total of 84% C-suite executives believe they must leverage AI to achieve their growth objectives and fear if they don’t scale this technology in the next five years, they risk going out of business.
Nail it, then scale it
Accenture’s report; AI: Built to Scale, aims to help companies progress on their AI journey, from a one-off AI experimentation to gaining a robust capability.
Three distinct company groups emerged from the research. These included:
Proof of concept
- Analytics buried deep
- Siloed operating model typically IT-led
- Unable to extract value from their data
- Struggle to scale due to unrealistic time expectations
- Significant under investment
Accenture report, 80-85% of companies are at this stage.
- CEO focused with advanced analytics and data team
- Multi-disciplinary teams of 200+ specialists
- Able to tune out data noise
- Intelligent automation and predictive reporting
- Catch up on digital/AI/data asset debt
- Experimental mindset achieving scale and returns
Accenture report 15-20% of companies have progressed to this vital stage.
According to the study less than 5% of companies have evolved to being industrialised for growth which includes:
- Digital platform and enterprise culture of AI democratising real-time insights to drive business decisions
- Clear enterprise vision and accountability breaking down silos
How to succeed at scaling
The research revealed three critical success factors separate the strategic scalers from organisations at the proof of concept stage.
- Drive ‘intentional’ AI
According to the survey scalers pilot more initiatives than those at the proof of concept stage and set longer timelines. They are 65% more likely to report a timeline of one to two years to move from pilot to scale and achieve more by spending less.
“At first glance it may seem paradoxical. But the data indicate that these leaders are more intentional, with a more realistic expectation in terms of time to scale.”
To successfully scale, companies need structure and governance in place. A total of 71% say they have a defined strategy and operating model while only half of the companies in proof of concept report the same. Owners with clear accountability and established leadership support with dedicated AI champions is also critical for success.
2.Tune out data noise
The survey shows strategic scalers can tune out data noise and are able to focus on financial, marketing, consumer and master data as priority domains.
Strategic scalers are also better at managing data. The Accenture research shows they have an accurate data set (61% versus 38% of respondents in proof of concept) and use the correct AI tools such as cloud-based data lakes to manage the data for their applications
“From creation to custodianship to consumption. Strategic scalers understand the importance of using more diverse datasets to support initiatives,” reveals the report.
- Treat AI as a team sport
The introduction of multi-disciplinary teams throughout an organisation is adopted by 92% of strategic scalers.
“Embedding them across the organisation is not only a powerful signal about the strategic intent of the scaling effort, it also enables faster culture and behaviour changes,” concludes the report.