Published on the 15/10/2024 | Written by Heather Wright

Investment in generative AI and automation is meeting or exceeding expectations for many organisations, with the most advanced organisations achieving higher revenue growth, greater productivity and better success scaling use cases.

That’s according to a new report from Accenture, which surveyed 2,000 executives worldwide, including in Australia. But there are caveats attached, with the 2.5x higher revenue growth, 2.4x greater productivity and 3.3x greater scaling success for genAI use cases happening for an elite group who have achieved what Accenture dubs the ‘reinvention-ready’ stage.

“More than 20 use cases are now being tested across NAB, and are showing ‘compelling’ results.”

That’s a point where an organisation has a fully modernised data foundation and end-to-end platform integration that supports hyper-automation across most processes. Also a pre-requisite for reinvention-ready organisations is the application of traditional AI to augment tasks at scale and rapid scaling of gen AI use cases.

Just 16 percent of companies surveyed globally had achieved that level of ‘fully modernised, AI-led processes’, aka intelligent operations.

An added caveat: The revenue increase, productivity gain and scaling boost figures cited in the report compare the reinvention-ready companies with peers with the lowest operations readiness – a category where eight percent of organisations languish.

In between are the big categories of automated companies (56 percent) and insights-driven organisations (20 percent).

Gen AI hype has receded somewhat this year, with the tech reaching the peak of inflated expectations in Gartner parlance, and many companies struggling to find the promised transformative benefits of gen AI.

Arundhati Chakraborty, Accenture Operations group chief executive, says generative AI requires organisations to have a strong digital core, data strategy and a well-defined roadmap to change the way they operate.

On the tech front, the research indicates many are lagging on building a robust data foundation. Sixty-one percent say their data assets are not ready for generative AI yet, and 70 percent find it hard to scale projects that use proprietary data.

Implementing a centralised data governance and domain-centric approach to data modernisation is a key step for businesses wanting to attain that ‘reinvention ready’ status, the report says.

It requires connecting processes and tools across functions to ensure people have a clear understanding of how to create, handle and consume data, which should be structured in a standardised way to be accessed by AI tools across the business.

“These are the hallmarks of a modern data foundation. And it’s where most companies struggle. Modernising the data foundation takes a significant amount of time and resources.”

The survey found that 71 percent of ‘foundational organisations’ – the eight percent at the bottom of the back where automation hasn’t begun or is in very early stages and where there is no AI strategy and data is siloed and mainly analysed for historical reporting – don’t have a data foundation modernised enough to get the full value of gen AI across the organisation.

“Access to quality data is a key consideration. More than one in three reinvention-ready organisations enable high-speed access to quality data and metadata assets that are free of inconsistencies and redundancies. This is made possible by placing equal responsibility on business teams and domain experts to modernise the data foundation.”

The majority (87 percent) of reinvention-ready companies are also adopting cloud-based practices such as cloud-based process mining to calibrate internal and external benchmarking and visualise process gaps.

“This can speed gen AI adoption by providing clear insights into operational inefficiencies while flagging opportunities for improvements. Organisations get the data they need to analyse their processes and identify areas where AI can add the most value.”

With accurate benchmarks, companies can set realistic targets and simulate the impact of AI interventions using digital twins, providing a data driven approach that ensures initiatives are aligned with strategic goals.

The report also notes that a deep dependency on people is often overlooked by companies. Eighty-two percent of companies at the early stage of operations maturity haven’t applied a talent reinvention strategy, planned to meet workforce needs, or acquired the new talent or training to prepare workers for generative AI-led workflows.

The report urges companies to embrace a ‘talent-first reinvention strategy’, rethinking processes and workflows to gain a clear view of where generative AI can have the most impact.

“Many companies are making ‘no regret’ AI investments and seeing some early wins in areas like software coding, automated content creation, financial reporting and knowledge retrieval,” the Reinventing Enterprise Operations with Gen AI report says.

A smaller, but growing number of companies are making longer-term strategic investments that offer truly novel competitive advantages for driving business growth and reducing operating costs.

But the real standouts, the report says, are transforming their digital core and modernising their data foundation to ‘super-charge’ their use of gen AI.

“These reinvention-ready organisations are deploying gen AI everywhere and transforming the value chain in R&D, HR, legal, supply chain, marketing, customer services, engineering design, manufacturing and other core functions.”

The survey shows the reinvention-ready companies have developed generative AI use cases in IT (75 percent), marketing (64 percent), customer service (59 percent), finance (58 percent), R&D (34 percent) and other core functions.

The report highlights NAB’s use of gen AI. The bank has been assessing ideas and opportunities with gen AI through several lenses, shortlisting ideas and moving them into test and development cycles to ascertain the projects with the greatest value, return and impact for customers.

“Strict data and AI guardrails are applied to embed safety from day one.”

More than 20 use cases are now being tested across NAB, and are showing ‘compelling’ results.

“Legal document reviews have been cut down from three days to one and higher-quality code is being developed faster. Simplified, automated processes are also improving customer outcomes.”

Accenture is, of course, invested in seeing AI boom. Last month the company reported stronger than expected fiscal 2024 Q4 earnings, driven by increased demand for services to help companies implement gen AI technology.

Revenue from gen AI deployments surged to US$900 million, from $100 million a year earlier with gen AI bookings sitting at $1 billion for the quarter and $3 billion for the year.

Earlier this year an Accenture report for Microsoft claimed the adoption of gen AI could add NZ$76 billion per year to New Zealand’s economy by 2038.