by For tech-savvy businesses and organizations, new developments in GenAI technology are expected to open up even more revolutionary possibilities.
These changes occur at a time when evidence indicates that, despite the fact that the GenAI boom is real and that optimism is high, not all organizations are currently producing noticeable value.
Even though only 43% of the C-suite strongly think that current solutions are fulfilling expectations, 97% of CEOs expect a meaningful impact from the technology, and 99% of respondents want to increase their investment in GenAI, according to NTT DATA’s Global GenAI Report.
But as agentic AI advances, this will soon change as strong use cases emerge that will not only increase revenues but also alter how businesses function and employees perform their duties.
The dial is shifted by agentic AI.
According to research by NTT DATA, 95% of organizations concur that technology is fostering a new degree of creativity and innovation, and agentic AI represents a significant advancement in the development of GenAI.
Agentic AI is capable of carrying out activities within workflows, going much beyond the basic question-and-answer capabilities of current technologies. The technology is capable of independent operation, decision-making based on real-time analysis, and—most importantly—execution.
Value will be unlocked and company operations will be completely transformed thanks to this capacity to “think” and act independently.
Potential applications of agentic AI
Agentic AI is beginning to appear in real-world applications across a range of industries, including automated trading systems, autonomous cars, healthcare, and the natural sciences. These systems will be designed to carry out tasks, make decisions, and engage with their surroundings in a manner that emulates human agency.
For instance, AI-powered diagnostic technologies will be used more frequently by hospitals and other healthcare professionals to help with disease identification and medical image processing.
Agentic agents will eventually oversee the entire customer engagement process in the insurance industry. For instance, in response to a client request, an AI assistant may finish intricate tasks and update customer data with pertinent information.
Five suggestions for success
How can businesses maximize value generation and guarantee a seamless deployment as they seek to include agentic AI into their operations? NTT DATA, who are specialists in agentic AI, has determined five key success factors:
- incorporation. A complete stack of services and technology includes smart agents. Agentic AI must be combined with other technologies and activities in order for organizations to get the transformative benefits they want. To successfully respond to encounters and produce significant results, it is insufficient on its own.
- alignment. To satisfy their unique use case and commercial needs, organizations must strike the correct technological balance. GenAI, for instance, needs to be viewed as a fundamental component of the business plan itself. According to a study by NTT DATA, 51% of respondents believe that this strategic alignment has not yet been fully attained.
- Getting ready. Success depends on data governance and preparedness, which must be addressed concurrently with business process transformation. To help organizations realize value gradually, NTT DATA suggests a staggered data transformation methodology.
- Activities. For all organizations to maintain and enhance agentic models, prevent model drift, set boundaries, and develop a strong user feedback loop to control agent workflow, mature AIOps will be essential. When organizations weigh the autonomy of specific decisions, human involvement will be a major factor.
- collaborations. Seek out partners who support smart-agent ecosystems and unique third-party services that contribute to the development of mid- and long-term competitive advantages. With access to the newest technology, being able to tap into such ecosystems will assist in derisking and expediting agentic AI creation.
Although adoption of agentic AI is still in its infancy, it will pick up speed quickly. The moment has come to begin establishing use cases, coordinating prepared materials, and finding collaborators who can help your smart-agent deployments succeed.
