Presenting October.ai—Agentic Cloud
AI Agents Are Changing the Face of Business with Autonomous Engine.
Capitalize on the AI Agent Opportunity
How to implement AI agents to transform business models.
Generative AI (GenAI) is transforming industries by enabling machines to create human-like text, images, and code with speed and accuracy. Businesses use GenAI for content creation, automation, and customer engagement, driving productivity and innovation.
AI Agents are the next big leap—autonomous systems that reason, plan, and execute tasks in real time. Unlike traditional automation, they adapt, learn, and make decisions with minimal human input, revolutionizing business automation, customer service, and workflow optimization.
By 2028,
33% of enterprise software will include agentic AI.
AI agents are autonomous or semi
autonomous software entities that use AI
techniques to perceive, make decisions,
take actions, and achieve goals in their
digital or physical environments.
What AI Agents Are NOT
- Large Language Models (they are models)
- Set of instructions/subroutines
- Automated software functions
- RPA Workflow automations
- Conversational Assistants or UX interfaces to them
The Big Pivot: AI Agents in Action
From process to progress — reaching Action with Agency
Augmentation
Automation
Autonomy
The Big Pivot: AI Agents in Action
From process to progress — reaching Action with Agency
Augmentation
Automation
Autonomy
C-Suite View of AI Agents
Current AI Systems
Require (strong) supervision
Execute (relatively) simple tasks
Static behaviour
Future AI Systems
Act Autonomously
Execute on complex goals
Adaptable behaviour
C-Suite View of AI Agents
Current AI Systems
Require (strong) supervision
Execute (relatively) simple
tasks Static behaviour
Future AI Systems
Act Autonomously
Execute on complex goals
Adaptable behaviour
Business Value of Agentic AI
Business agility
Scale
Quality / Resiliency
Labour speed
AI Agent Platforms
User Permission
- Agent Monitoring and Governance
- Prebuilt Agents Natural Language Build - Engineer Build
- Prebuilt or Al Agent Built Tooling to Retrieve Data and Act
- Curated Data Layer - SaaS-KBs, KGs, Long Term Memory
- Models -BYOM, LAM, NSM, LLM - Access to Al Techniques
Evaluating a Use Case for
October.ai—Agentic Cloud.
- Sales, Marketing, Customer Service
- Field Service and Operations
- Contract Lifecycle Management
- Employee Engagement
- Experience Orchestration
- Project and Task Management
AI Prism Chart
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