Who should enter the ‘Best Agentic AI Solution‘ category?

The ‘Best Agentic AI Solution’ category category recognizes outstanding solutions that use agentic AI to take action towards defined goals. It is open to individual AI agents, multi-agent systems, agentic platforms and frameworks that demonstrate meaningful agency in how they approach and complete work.

Agentic solutions demonstrate the capacity to adapt their approach as new context emerges, operational conditions change, or unexpected obstacles arise.

Entrants should clearly explain what decisions the AI can make, what actions it can perform, how independently it can operate, and what it can accomplish as a result.

Solutions might interact with tools, APIs, software applications, enterprise systems or data sources in order to complete tasks, with the AI determining some or all of the actions required.

Entrants do not need to demonstrate every possible characteristic of agentic AI to be eligible. A focused agent that independently handles a clearly defined task may be just as compelling as an extensive network of collaborating agents.

Submissions are welcomed from any industry or field of application (e.g. engineering, cybersecurity, financial operations, sales, supply chain, among others), or entirely new applications made possible by agentic AI.

IT team building agentic AI solution

Example Use Cases

Applications of agentic AI include, but are not limited to, the following example areas:

Team working with graphs and data on laptops and tablets at office table

Agentic AI can take responsibility for operational tasks that involve several stages, systems or decisions. Agents can assess the state of a task, determine what needs to happen next and take permitted actions until an objective is reached or human input becomes necessary.

Typical use cases:

  • Managing business requests or cases from receipt through to resolution
  • Gathering information from multiple systems before determining subsequent actions
  • Handling routine exceptions and selecting appropriate responses
  • Coordinating tasks, approvals and updates across business applications

Demonstrable outcomes include:

  • Reduction in manual interventions per process
  • Shorter end-to-end completion times
  • Higher proportion of eligible work completed autonomously

software developers working on multiple screens displaying code and application diagrams in a modern office

Agentic AI innovation does not have to be delivered as a single end-user application. Platforms and frameworks may provide the underlying capabilities required to build, deploy, coordinate and govern agents across multiple use cases, particularly where organizations need agents to operate reliably at scale.

Typical use cases:

  • Providing environments for creating and deploying task-oriented AI agents
  • Connecting agents securely with enterprise tools, APIs and data
  • Managing agent permissions, context, memory and available capabilities
  • Supervising agent activity, hand-offs, evaluations and human approval points

Example measurable outcomes include:

  • Reduced time required to develop or deploy new agentic applications
  • Increased number of agents or workflows supported at scale
  • Improvements in reliability, governance or successful task completion

business-idea-office-laptop

Agentic research systems can pursue an information objective through multiple stages rather than responding to a single query. An agent may determine what information is required, investigate different sources, identify gaps or conflicting evidence, conduct further enquiries and assemble its findings into a usable result.

Typical use cases:

  • Conducting multi-stage commercial, scientific or technical research
  • Identifying gaps in available evidence and initiating further investigation
  • Comparing and validating information from multiple sources
  • Adjusting research priorities as new findings emerge

Example measurable outcomes include:

  • Reduced researcher time per completed assignment
  • Greater breadth of relevant information evaluated
  • Faster production of actionable research or intelligence

AI to improve employment pipelines in DevOps

AI agents can diagnose operational problems and pursue their resolution across complex IT environments. Instead of relying solely on a fixed remediation script, the AI can use available evidence to determine an appropriate course of action, assess whether it worked and change its approach when necessary.

Typical use cases:

  • Diagnosing infrastructure, application or service problems
  • Selecting and executing appropriate remediation procedures
  • Fulfilling routine IT service requests across connected systems
  • Assessing the result of an intervention and initiating further action where required

Measurable outcomes may include:

  • Lower mean time to resolution
  • Fewer incidents requiring manual intervention
  • Reduced operational workload for IT teams

Agentic customer service solutions can progress from answering questions to actively resolving customer needs. An agent might investigate a problem, access relevant systems, decide what action is appropriate and execute authorized changes, while referring sensitive or exceptional cases to a human representative.

Typical use cases:

  • Investigating customer issues across account, order and service systems
  • Carrying out authorized refunds, replacements or account changes
  • Managing multi-stage enquiries requiring several actions to resolve
  • Escalating cases when confidence, permissions or policy thresholds are reached

Example measurable outcomes include:

  • Increased end-to-end resolution without agent hand-off
  • Reduced average time to resolve customer issues
  • Improved customer satisfaction or first-contact resolution

Areas to Highlight in Your Submission

Judges score nominations across these five key areas:

  • Innovation: The features or technology that makes your agentic solution unique - or transformed your market.

  • Impact: Evidence of the positive effect your agentic solution has brought to your customers or users.

  • Scalability: How your solution grows or adapts to changing business needs, without significant upgrades or overhauls.

  • User Experience: How intuitive your agentic solution is to use for users of varying roles or skill levels.

  • Relevance: What makes your solution a worthy winner in this particular category.

Although not formally scored, focus on these areas specific to this category, can help your nomination stand out:

Sophistication

Discuss the complexity of the problem vs the elegance of the agentic AI solution

Safeguards

The protections in place that recognize when human judgement is needed.

Reliability

The confidence and consistency in the agentic solution's output and process

More A.I. Awards Categories

Next Steps to Enter The A.I. Awards

To enter this AI Awards category, or any other category in The AI Awards, please follow these three simple steps:

  • Download the entry form. Open up the ‘AI Awards Simple Form’ document.

  • Complete the form. You only need to complete the form once, even if entering multiple A.I. Awards categories.

  • Submit your entry. Head to the ‘Submit Now’ section on our website, select ‘The A.I. Awards’ and the category/categories you are entering from the list, upload your form and any other materials you would like the judges to review, and process your fees.

The A.I. Awards is a program from The Cloud Awards. Since 2011, we’ve been helping organizations across the globe gain the recognition they deserve for market-leading innovation in the cloud computing and software sectors.

For a detailed breakdown of all the benefits you receive as an awards entrant as either a shortlistee, finalist or ultimate winner, please see our “Why Enter?” page. The many benefits are replicated across all international awards programs. If you have any questions about this category, please contact us.