Businesses can accelerate growth and optimize operations by re-engineering systems for AI operations, according to an Accenture report on AI readiness and digitalization strategies.
The report noted companies that strategically invest in innovation can redesign business processes, launch new products, and enter new markets more effectively.
Additionally, tailoring digital core advancements to specific needs can trigger automatic improvements in other areas, making it easier to achieve an industry-leading digital capability for continuous reinvention.
The report also noted balancing technical debt with future investments is crucial; organizations should allocate 15% of IT budgets and use programmatic and autonomous methods to reduce debt while ensuring the maintenance of evergreen IT capabilities.
Andy Tay, global lead of Accenture Cloud First, said companies must conduct a comprehensive assessment across seven digital core components to establish a view of current capabilities.
The seven components in their estate are digital platforms, integration, AI, data foundation, cloud-first infrastructure, continuum control plane and security.
“Whether you use our diagnostics or another proprietary method, these are the top areas for companies to identify low-hanging fruit improvement areas,” he said. “Every company is different, so every digital core journey will be different. That’s why conducting that upfront assessment and building a personalized roadmap are key.”
Tay noted technical debt—the accumulated cost from legacy code and quick IT fixes–has long been a problem.
“We saw a lot of hasty cloud migrations and modernization efforts that resulted in more debt because these moves were made absent the solid technical foundation needed for long term success,” Tay explained. “That’s why companies need a more strategic approach to innovation going forward.”
He said investing in controlling technical debt ensures innovation efforts result in long term value rather than just short-term wins.
From Tay’s perspective, addressing technical debt is a balancing act: It’s necessary to mitigate baggage of the past, while avoiding dragging down your investments in the future.
“The amount that you need to invest in tech debt remediation is a function of where you’re at, and where you want to go,” he said.
For example, innovating with GenAI is on everyone’s mind, but Accenture research found AI is the top contributor to tech debt, tied with applications.
“However, GenAI can also be deployed as a tool to manage and mitigate tech debt,” he said. “If adopted strategically, you can reach that balance of managing debt and moving the needle on future tech.”
Managing tech debt in a way that supports innovation will always require a commitment to continuous updates, upgrades and management.
“We see companies using more programmatic and autonomous methods to lighten this lift,” Tay explained. “For example, programmatic version control systems can be used to update configuration settings for infrastructure following changes to the code.”
When it comes to measuring the effectiveness of their IT spend on innovation versus operations, Tay said it’s about intention and execution—knowing the desired business outcome.
“Every company measures their own success uniquely,” he said. “One of the common barriers is IT and business misalignment and stalled desired outcomes. Ensuring common and clearly understood goals is critical to any attempt to measure effectiveness.”
Another consideration is the horizon over which the innovation investments are intended to come to fruition.
Tay noted long horizons will naturally be more difficult to measure than more clearly defined near-term investments such as modernization activities like decoupling large legacy applications and moving elements to the cloud.
“The old saying rings true every time – measure twice, cut once,” he said. “Be intentional on what you need to measure, get the best people and tools to do the job, and go for it.”
