KUALA LUMPUR (October 14): Agent-based artificial intelligence (AI) is positioned as a valuable tool for enterprises to maintain a competitive edge, but its implementation into business operations requires long-term consideration to ensure optimal value is extracted.
Agenttic AI refers to AI systems designed to understand context, solve complex problems, and make decisions independently. This will enable entire workflows from supply chain to marketing to product development to be managed with live, intelligent decision-making without excessive human intervention.
“This reflects a broader trend: Organizations are no longer experimenting with individual use cases, but are building integrated ecosystems of AI agents that can learn, adapt and collaborate like digital teammates,” said Azwan Baharuddin, Country Managing Director, Accenture Malaysia.
“Instead of grappling with technical complexity, enterprises can deploy agents that reduce time to market, increase automation, and scale innovation across functions.”
When implementing agent AI, one of the key areas where companies should accelerate their investments is in addressing the digital core of the business. This means that it is important for companies to have the right and up-to-date technology infrastructure to quickly adapt to new developments in the AI environment.
“We encourage businesses to focus on strengthening their digital core through cloud, data and security to make it easier for them to deploy advanced AI capabilities,” Azwan said.
While the impact of agent AI is expected to transform every sector, one industry that is seen to benefit greatly from this technology is the banking sector. According to Accenture's report titled “Banking on AI,” agent AI has the potential to improve productivity by 22% to 30% and increase revenue by up to 6% through operational efficiency.
These efficiencies come from three key changes that allow AI to work in multi-agent ecosystems, drive intelligent end-to-end automation, and evolve from performing static operations to making data-driven decisions.
Azwan also believes that small and medium-sized enterprises (SMEs) can greatly benefit from agent AI, but it will depend on each SME's industry, digital readiness, and business priorities.
In addition to addressing the digital core, there are two other investment areas to consider to leverage agent AI. By focusing on developing AI operating models, we can integrate multi-agent systems that can learn, reason, and act to give companies a clearer picture of their internal AI ecosystem.
Trust and governance are also factors that need to be carefully considered, as establishing a clear framework around explainability, ethics, and human-AI collaboration will ensure a safe and stable environment for both business operations and employee culture.
According to a study conducted by Accenture, 85% of Malaysian executives believe that AI agents will reinvent the way digital systems are built, but only 41% expect their usage to increase significantly within the next three years.
Additionally, 76% of global IT executives identify IT as the key area for generative AI transformation over the next three years, with efficiency gains expected to be around 23%.
“While these results demonstrate intent, enterprises are still in the early stages of laying the foundations to support new trends in digital transformation,” Azwan explains.
To further preserve the longevity of agent AI, instill practices that integrate AI into core operations while focusing on sustainable, high-impact outcomes.
“One of the most strategic and no-regret moves you can make is to start by transforming your IT function. Once you have a robust digital core in place, the next question is where to apply AI, especially generative AI, to have the greatest impact on your business,” he says.
However, Azwan cautions that companies should be careful when applying agent-based AI automation, as it can introduce unintended risks to operational stability, beyond just cost savings and automation.
For example, IT functions such as disaster recovery and complex network management are critical to business continuity, but the payoff, for better or worse, is not always immediate, and disrupting such work flows can be costly for businesses.
As technology transforms, we must not ignore the importance of human involvement. The increased use of AI will lead to job losses, but it will also lead to future job redefinition.
The key to addressing this, Azwan says, is to proactively identify roles impacted by AI and implement targeted reskilling strategies.
“A culture of continuous learning is essential to not only keep up with advances in AI, but also to enable employees to grow with them. In doing so, companies not only unlock productivity and innovation, but also foster resilience in their workforce. This dual investment in AI and talent ensures that organizations can scale responsibly,” he shares.
