As the initial frenzy around Generative AI shifts to new agentic and automation use cases, enterprises must embrace a holistic and orchestrated approach to achieve meaningful productivity gains.
Enterprises are adapting and deploying GenAI and AI agents across the enterprise. Gartner estimates that by 2028, 33% of enterprise software will include agentic AI, up from less than 1% in 2024. This means 15% of day-to-day work decisions could be made autonomously, according to the research.
The benefits are clear: AI agents facilitate autonomous decision-making and the ability to perform tasks independently. At the same time, they also augment human workers to empower decision-making and drive greater efficiency. Despite the many upsides, however, many companies are struggling to turn the performance gains of individual workflows into systematic enterprise-scale productivity advantages.
As agentic AI proliferates, the lack of effective governance, integration, and orchestration strategies can lead to increased fragmentation and sprawl, making it harder to achieve impactful efficiencies and measurable business value. With heterogeneous business applications and systems in the mix, it’s difficult to seamlessly integrate AI agents and automation across diverse workflows and data silos.
IBM’s differentiated approach to AI agents and productivity
IBM’s focus on AI assistant and agent orchestration, and prebuilt integrations weaves agentic AI into the enterprise fabric. This elevates individual use cases and tasks to solutions that work collectively to deliver business value. Critical to IBM’s agentic AI vision is an orchestration layer that facilitates integration, communication, and information sharing. The orchestration layer allows for the right data to be sent to the right agents at the right time, encapsulated with the proper context and security models. This is crucial to unleashing multiple agents to successfully solve problems and complete complex tasks.
Unlike competitors with similar agentic AI offerings, IBM emphasizes an open, hybrid approach. This enables organizations to address the complexities of a heterogeneous IT landscape by managing the development and deployment of custom and third party-built AI agents through a single, unified experience. IBM’s deep roots in enterprise integration drives AI agents and assistants to work seamlessly across a broad landscape that encompasses business workflows, business applications, and diverse data sources.
“IBM is focused not just on building an ecosystem of things that fly in formation, but on integration with critical enterprise platforms such as SAP SuccessFactors, Salesforce, and ServiceNow,” says Matt Sanchez, Vice President, Product, watsonx Orchestrate at IBM.
As “client zero,” IBM has put its highly orchestrated, AI approach to work within its own organization. Examples include:
AskHR, a conversational AI solution which automates more than 80 common HR processes and answers 94% of common employee HR inquiries in minutes without human intervention.
Using AI digital assistants for customer care that now resolve 70% of customer support inquiries, accelerating time to resolution by as much as 26% and boosting customer satisfaction.
AskIT, a self-service system created using AI and natural language processing (NLP) capabilities to surface resolutions to critical support topics, can address 80% of IBM’s top IT issues.
The bottom line
Agentic AI is poised to raise productivity across every aspect of business. Yet without a plan for integration and orchestration, enterprises may benefit from workflow efficiencies while missing the broader opportunity for strategic business transformation. IBM has the deep expertise and hands-on knowledge to turn agentic AI into successful business transformation.
To learn more about how IBM can help you orchestrate AI across your business, visit IBM watsonx Orchestrate.