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AI & Innovation

Agentic Thinking

In a world where AI is rapidly evolving from passive assistants to autonomous agents, agentic thinking is emerging as a critical leadership mindset. This presentation explores how leaders can harness the power of AI agents to transform their organizations, drive innovation, and create the enterprise of the future.

Evolution

Evolution

From Automation to Agentic AI

Consumer "do-everything" agents are still uneven; enterprises win by starting with high-value, bounded use cases and strong governance.

Agentic AI refers to systems with agency – the ability to independently plan and execute tasks in pursuit of goals. Unlike traditional software or basic AI assistants, these intelligent agents can:

  • Handle entire workflows end-to-end

  • Collaborate with other agents

  • Adapt based on real-time data

Over 80% of executives plan to integrate AI agents in their operations within three years, seeing them as key to scaling productivity and business impact.

Predictive AI

Shows what might happen

Generative AI

Creates content on demand

Agentic AI

Takes action on our behalf

Agentic thinking is the leadership approach of envisioning and structuring work in terms of autonomous agents. It means designing business processes as networks of AI "co-workers" that can take initiative, make rule-based decisions, and continuously learn, all under appropriate human oversight.

High-value cases

Industry Applications of Agentic AI

Energy

Asset health monitoring agents watch over equipment in real time. One pipeline operator saw a 60% reduction in manual inspections and 30% faster leak response, saving £5M annually.

Healthcare

AI agents act as virtual care coordinators, guiding patients through pre-visit prep, in-visit support, and post-visit follow-up. Administrative agents handle scheduling, billing and claims, reducing processing times from weeks to days.

Finance

AI trading agents monitor market data 24/7, parse news feeds, adjust strategies, and execute trades in real time. Personal finance agents autonomously manage aspects of a customer's finances to optimize financial health.

Pharma

Insilico Medicine used AI agents to design a novel drug for pulmonary fibrosis, going from target to clinical trials in under 18 months – a fraction of the usual time.

Insurance

AI claims agents enable "touchless" claims that settle within hours. Some insurers report simple auto claims being paid out in under 3 hours, vastly improving customer satisfaction.

High-value cases

Industry Applications of Agentic AI

Energy

Asset health monitoring agents watch over equipment in real time. One pipeline operator saw a 60% reduction in manual inspections and 30% faster leak response, saving £5M annually.

Healthcare

AI agents act as virtual care coordinators, guiding patients through pre-visit prep, in-visit support, and post-visit follow-up. Administrative agents handle scheduling, billing and claims, reducing processing times from weeks to days.

Finance

AI trading agents monitor market data 24/7, parse news feeds, adjust strategies, and execute trades in real time. Personal finance agents autonomously manage aspects of a customer's finances to optimize financial health.

Pharma

Insilico Medicine used AI agents to design a novel drug for pulmonary fibrosis, going from target to clinical trials in under 18 months – a fraction of the usual time.

Insurance

AI claims agents enable "touchless" claims that settle within hours. Some insurers report simple auto claims being paid out in under 3 hours, vastly improving customer satisfaction.

High-value cases

Industry Applications of Agentic AI

Energy

Asset health monitoring agents watch over equipment in real time. One pipeline operator saw a 60% reduction in manual inspections and 30% faster leak response, saving £5M annually.

Healthcare

AI agents act as virtual care coordinators, guiding patients through pre-visit prep, in-visit support, and post-visit follow-up. Administrative agents handle scheduling, billing and claims, reducing processing times from weeks to days.

Finance

AI trading agents monitor market data 24/7, parse news feeds, adjust strategies, and execute trades in real time. Personal finance agents autonomously manage aspects of a customer's finances to optimize financial health.

Pharma

Insilico Medicine used AI agents to design a novel drug for pulmonary fibrosis, going from target to clinical trials in under 18 months – a fraction of the usual time.

Insurance

AI claims agents enable "touchless" claims that settle within hours. Some insurers report simple auto claims being paid out in under 3 hours, vastly improving customer satisfaction.

Benefits

Benefits

Benefits

The Case for Agentic Thinking

Agentic thinking addresses the dual mandate of modern leadership: drive efficiency today while building capacity for innovation tomorrow.

Autonomous agents can handle tasks 24/7 without fatigue, dramatically scaling operations. A single AI claims agent can settle insurance claims in hours versus days, allowing one department to handle double the volume without more staff.

Autonomous agents can handle tasks 24/7 without fatigue, dramatically scaling operations. A single AI claims agent can settle insurance claims in hours versus days, allowing one department to handle double the volume without more staff.

Autonomous agents can handle tasks 24/7 without fatigue, dramatically scaling operations. A single AI claims agent can settle insurance claims in hours versus days, allowing one department to handle double the volume without more staff.

Autonomy = Scale and Speed

Business processes are increasingly complex. Agentic AI is uniquely suited to manage such complexity because it can make real-time decisions and coordinate actions across systems without constant human intervention.

Business processes are increasingly complex. Agentic AI is uniquely suited to manage such complexity because it can make real-time decisions and coordinate actions across systems without constant human intervention.

Business processes are increasingly complex. Agentic AI is uniquely suited to manage such complexity because it can make real-time decisions and coordinate actions across systems without constant human intervention.

Business processes are increasingly complex. Agentic AI is uniquely suited to manage such complexity because it can make real-time decisions and coordinate actions across systems without constant human intervention.

Complexity Requires Automation

AI Agents are adaptive – they learn from each outcome and improve over time. This self-improving capability means processes guided by AI agents get better and more efficient with experience.

AI Agents are adaptive – they learn from each outcome and improve over time. This self-improving capability means processes guided by AI agents get better and more efficient with experience.

AI Agents are adaptive – they learn from each outcome and improve over time. This self-improving capability means processes guided by AI agents get better and more efficient with experience.

Continuous Improvement

By offloading rule-based decisions and repetitive tasks to AI, organizations can alleviate employee burnout and repurpose talent towards innovation. AI is the co-pilot, not the pilot.

By offloading rule-based decisions and repetitive tasks to AI, organizations can alleviate employee burnout and repurpose talent towards innovation. AI is the co-pilot, not the pilot.

By offloading rule-based decisions and repetitive tasks to AI, organizations can alleviate employee burnout and repurpose talent towards innovation. AI is the co-pilot, not the pilot.

Human Talent Optimization

Validation

Readiness Checklist

Evaluate your agentic AI initiative against these criteria.

Strategic Fit

  • Single OKR the agent moves; mapped to CFO/COO metric.

  • Clear "value driver" linked to P&L line.

Data & Integration

  • System-of-record identified; data quality risks logged.

  • Integration path defined; manual fallback documented.

People & Process

  • Who will change what, when (RACI)?

  • Adoption incentives and training plan are funded.

Validation & Governance

  • Leading indicators, thresholds, and guardrails agreed pre-launch.

  • Bias/drift monitoring and audit trail in place.

Validation

Readiness Checklist

Evaluate your agentic AI initiative against these criteria.

Strategic Fit

  • Single OKR the agent moves; mapped to CFO/COO metric.

  • Clear "value driver" linked to P&L line.

Data & Integration

  • System-of-record identified; data quality risks logged.

  • Integration path defined; manual fallback documented.

People & Process

  • Who will change what, when (RACI)?

  • Adoption incentives and training plan are funded.

Validation & Governance

  • Leading indicators, thresholds, and guardrails agreed pre-launch.

  • Bias/drift monitoring and audit trail in place.

Validation

Readiness Checklist

Evaluate your agentic AI initiative against these criteria.

Strategic Fit

  • Single OKR the agent moves; mapped to CFO/COO metric.

  • Clear "value driver" linked to P&L line.

Data & Integration

  • System-of-record identified; data quality risks logged.

  • Integration path defined; manual fallback documented.

People & Process

  • Who will change what, when (RACI)?

  • Adoption incentives and training plan are funded.

Validation & Governance

  • Leading indicators, thresholds, and guardrails agreed pre-launch.

  • Bias/drift monitoring and audit trail in place.

Successful implementations

Successful implementations

Successful implementations

Scaled Applications

Toyota's "O-Beya"

A "big room" of nine AI agents built on Azure OpenAI Service. Each agent is a domain expert (Engine Performance, Emissions Regulation, etc.) that collaborates to answer complex engineering questions, preserving knowledge of retiring experts.

Microsoft Copilot Studio

An end-to-end platform for enterprises to build their own conversational AI agents. Businesses can define an agent's knowledge sources, connect it to enterprise systems, and set its scope of tasks.

Autonomous Pipeline Monitoring

AI agents along a 1,200-mile pipeline collect sensor data, detect anomalies, and take action - adjusting valves, notifying controllers, and dispatching drones for inspection - all within minutes.

Envisioning

Establish the Vision and Case for Change

Key Insight: 4 in 5 executives plan to use AI agents in 3 years.

01

Painting the Vision

Describe a future where routine work is offloaded to AI, enabling employees to focus on strategic and creative initiatives. Ground this in your company's mission.

02

Building the Business Case

Quantify pain points and opportunities. Estimate potential gains (e.g., reducing claims processing cost by 30%, increasing revenue by responding to leads faster).

03

Aligning with Strategic Goals

Ensure the agentic initiative ties into top-level goals (growth, customer satisfaction, innovation, cost leadership).

Envisioning

Establish the Vision and Case for Change

Key Insight: 4 in 5 executives plan to use AI agents in 3 years.

01

Painting the Vision

Describe a future where routine work is offloaded to AI, enabling employees to focus on strategic and creative initiatives. Ground this in your company's mission.

02

Building the Business Case

Quantify pain points and opportunities. Estimate potential gains (e.g., reducing claims processing cost by 30%, increasing revenue by responding to leads faster).

03

Aligning with Strategic Goals

Ensure the agentic initiative ties into top-level goals (growth, customer satisfaction, innovation, cost leadership).

Envisioning

Establish the Vision and Case for Change

Key Insight: 4 in 5 executives plan to use AI agents in 3 years.

01

Painting the Vision

Describe a future where routine work is offloaded to AI, enabling employees to focus on strategic and creative initiatives. Ground this in your company's mission.

02

Building the Business Case

Quantify pain points and opportunities. Estimate potential gains (e.g., reducing claims processing cost by 30%, increasing revenue by responding to leads faster).

03

Aligning with Strategic Goals

Ensure the agentic initiative ties into top-level goals (growth, customer satisfaction, innovation, cost leadership).

Proof ROI

Start with Focused Pilots

~70% of digital innovation projects never scale to full deployments. The following guidelines help to avoid common pitfalls.

Select High-Impact, Low-Risk Use Cases

Look for processes that are relatively self-contained, rule-based, and have clear success metrics. Good candidates are often in back-office or support functions (IT helpdesk, invoice processing, basic customer FAQs).

Define Pilot Scope and Guardrails

Clearly define what the AI agent will and won't do. Establish human-in-the-loop checkpoints and success criteria: "Pilot success = agent resolves 50%+ of tickets with >90% satisfaction and no security incidents."

Form Interdisciplinary Pilot Teams

Include process owners, AI developers, data engineers, and end-user representatives. Having frontline staff collaborate helps incorporate real-world knowledge and gain buy-in.

Monitor, Iterate, and Celebrate Wins

Run the pilot for 4-8 weeks. Monitor performance closely, gather feedback, and make improvements. When a pilot hits its goals, communicate it: "Our new AI agent resolved 1,000 IT tickets in its first month, saving 500 hours of employee downtime."

Proof ROI

Start with Focused Pilots

~70% of digital innovation projects never scale to full deployments. The following guidelines help to avoid common pitfalls.

Select High-Impact, Low-Risk Use Cases

Look for processes that are relatively self-contained, rule-based, and have clear success metrics. Good candidates are often in back-office or support functions (IT helpdesk, invoice processing, basic customer FAQs).

Define Pilot Scope and Guardrails

Clearly define what the AI agent will and won't do. Establish human-in-the-loop checkpoints and success criteria: "Pilot success = agent resolves 50%+ of tickets with >90% satisfaction and no security incidents."

Form Interdisciplinary Pilot Teams

Include process owners, AI developers, data engineers, and end-user representatives. Having frontline staff collaborate helps incorporate real-world knowledge and gain buy-in.

Monitor, Iterate, and Celebrate Wins

Run the pilot for 4-8 weeks. Monitor performance closely, gather feedback, and make improvements. When a pilot hits its goals, communicate it: "Our new AI agent resolved 1,000 IT tickets in its first month, saving 500 hours of employee downtime."

Proof ROI

Start with Focused Pilots

~70% of digital innovation projects never scale to full deployments. The following guidelines help to avoid common pitfalls.

Select High-Impact, Low-Risk Use Cases

Look for processes that are relatively self-contained, rule-based, and have clear success metrics. Good candidates are often in back-office or support functions (IT helpdesk, invoice processing, basic customer FAQs).

Define Pilot Scope and Guardrails

Clearly define what the AI agent will and won't do. Establish human-in-the-loop checkpoints and success criteria: "Pilot success = agent resolves 50%+ of tickets with >90% satisfaction and no security incidents."

Form Interdisciplinary Pilot Teams

Include process owners, AI developers, data engineers, and end-user representatives. Having frontline staff collaborate helps incorporate real-world knowledge and gain buy-in.

Monitor, Iterate, and Celebrate Wins

Run the pilot for 4-8 weeks. Monitor performance closely, gather feedback, and make improvements. When a pilot hits its goals, communicate it: "Our new AI agent resolved 1,000 IT tickets in its first month, saving 500 hours of employee downtime."

Control

Data Foundation and Governance

Gartner predicts that by 2028, 25% of enterprise breaches will involve AI agent misuse. Strong governance is essential.

Technology Infrastructure

  • Centralize and cleanse data for agent access

  • Ensure IT architecture supports API integrations

  • Plan for computational capacity needs

  • Implement tools for continuous learning

Security and Compliance

  • Implement allow-lists of approved actions

  • Log every agent action for auditability

  • Ensure GDPR, HIPAA compliance

  • Create kill-switch mechanisms

Governance Framework

Decision Rights

Define what decisions agents can make autonomously vs. what requires human approval.

Ethical Guidelines

Develop AI ethics principles addressing fairness, transparency, and accountability.

Governance Structure

Form an AI governance council to review use cases and monitor performance.

Continuous Audit

Regularly sample agent decisions to ensure quality and fairness.

Control

Data Foundation and Governance

Gartner predicts that by 2028, 25% of enterprise breaches will involve AI agent misuse. Strong governance is essential.

Technology Infrastructure

  • Centralize and cleanse data for agent access

  • Ensure IT architecture supports API integrations

  • Plan for computational capacity needs

  • Implement tools for continuous learning

Security and Compliance

  • Implement allow-lists of approved actions

  • Log every agent action for auditability

  • Ensure GDPR, HIPAA compliance

  • Create kill-switch mechanisms

Governance Framework

Decision Rights

Define what decisions agents can make autonomously vs. what requires human approval.

Ethical Guidelines

Develop AI ethics principles addressing fairness, transparency, and accountability.

Governance Structure

Form an AI governance council to review use cases and monitor performance.

Continuous Audit

Regularly sample agent decisions to ensure quality and fairness.

Control

Data Foundation and Governance

Gartner predicts that by 2028, 25% of enterprise breaches will involve AI agent misuse. Strong governance is essential.

Technology Infrastructure

  • Centralize and cleanse data for agent access

  • Ensure IT architecture supports API integrations

  • Plan for computational capacity needs

  • Implement tools for continuous learning

Security and Compliance

  • Implement allow-lists of approved actions

  • Log every agent action for auditability

  • Ensure GDPR, HIPAA compliance

  • Create kill-switch mechanisms

Governance Framework

Decision Rights

Define what decisions agents can make autonomously vs. what requires human approval.

Ethical Guidelines

Develop AI ethics principles addressing fairness, transparency, and accountability.

Governance Structure

Form an AI governance council to review use cases and monitor performance.

Continuous Audit

Regularly sample agent decisions to ensure quality and fairness.

Outlook

Outlook

Outlook

Change Management and Future Vision

Agentic thinking is leadership's ticket to navigate this new era – those who grasp it will lead their organizations to "crank out high-value innovations" and thrive, while those who don't may be left playing catch-up.

Workforce Enablement

  • Communicate early and often about AI's role

  • Invest in AI literacy and upskilling

  • Redefine roles as agents take on tasks

  • Encourage experimentation and feedback

Scaling Up

  • Develop an enterprise-wide rollout plan

  • Create reusable agent components

  • Mature governance as usage grows

  • Continuously measure and share value

The organization of the future isn't one with no people, but one where people maximally leverage AI to achieve their goals.