C3.ai - Overview

Company Information

Business Model

C3.ai is an enterprise AI application software company that provides: 1. C3 AI Platform - End-to-end platform for developing, deploying, and operating enterprise AI applications 2. C3 AI Applications - Pre-built, industry-specific AI applications 3. C3 Generative AI - Domain-specific generative AI offerings

Corporate Profile

C3.ai delivers a family of fully integrated products that enable organizations to rapidly develop and deploy enterprise-scale AI applications. The company serves industries including oil and gas, manufacturing, financial services, defense, and healthcare.

Company Evolution

Timeline

Leadership Transition

In September 2025, C3.ai announced that Stephen Ehikian would succeed Thomas Siebel as CEO. Siebel stepped down due to health issues (autoimmune disease affecting vision). Siebel remains Chairman.

Current Status (FY2025)

• Annual Revenue: $389.1 million (up 25% YoY)
• Market Capitalization: ~$3-4 billion (2025)
• Cash Position: $742.7 million
• Customers: 444 (enterprise customers)
• Growth Focus: Agentic AI, generative AI, partner ecosystem

Industry Position

C3.ai positions itself as: - Enterprise AI pioneer - Claims invention of enterprise AI category - Model-driven architecture - Differentiated technical approach - Turnkey solutions - Pre-built applications vs. custom development - AI for industries - Deep vertical expertise

C3.ai - Background & Origins

Founder: Thomas M. Siebel

Early Life and Education

• Born: November 20, 1952, in Chicago, Illinois
• Education:
• University of Illinois at Urbana-Champaign - B.A. History (1975)
• University of Illinois at Urbana-Champaign - M.A. Computer Science (1983)
• University of Illinois at Urbana-Champaign - MBA (1983)
• Doctoral work: Studied under Nobel laureate James Heckman (did not complete PhD)

Pre-C3.ai Career

Oracle Corporation (1984-1990)

Siebel Systems (1993-2006)

Founded: January 1993 Business: Customer Relationship Management (CRM) software IPO: June 1996

Key Milestones: - Pioneered CRM software category - Reached $2 billion in revenue - Became fastest-growing software company of its era - Acquired by Oracle: January 2006 for $5.85 billion

Siebel’s role: Chairman and CEO throughout

Post-Siebel Systems

Founding C3.ai (2009)

The Initial Idea

In January 2009, Tom Siebel founded C3 Energy with the vision of applying advanced analytics and machine learning to energy management.

Core thesis: - Smart grid and smart meter data would explode - Utilities needed AI to manage complex systems - Energy efficiency could be dramatically improved through data

Early Focus: Energy Sector

Key Early Customers

• PG&E - Pacific Gas & Electric
• Exelon - Major U.S. utility
• Shell - Oil and gas

Company Name Evolution

C3 Energy (2009-2016)

Origin of name: - “C” - Carbon - “3” - Third industrial revolution (digital transformation) - “Energy” - Initial market focus

C3 IoT (2016-2019)

Renaming rationale: - Expanded beyond energy to manufacturing, aerospace, healthcare - Internet of Things (IoT) was buzzword of the era - Platform applicable to any IoT use case

C3.ai (2019-Present)

Final rebranding: - Artificial Intelligence became the focus - AI hype cycle peaking - IPO preparation - Clearer market positioning

Early Funding and Growth

Funding Rounds

Total Pre-IPO Funding

Approximately $350 million raised before 2020 IPO

Investor Base

• Tom Siebel (significant personal investment)
• TPG Growth / The Rise Fund
• InterWest Partners
• Various strategic investors

Technical Architecture Development

Model-Driven Architecture

C3.ai’s core innovation was developing a model-driven architecture for enterprise AI:

Key concepts: - Data models - Abstract representation of business entities - Analytics models - Reusable analytical components - Application models - Configurable application logic - Deployment models - Infrastructure abstraction

Patent Portfolio

C3.ai has filed numerous patents, including: - Data integration methods - Machine learning pipelines - Model-driven application development - Agentic AI patent - Filed December 2022; awarded for generative AI

Early Customer Success

Baker Hughes Partnership (2019)

Announced: Strategic partnership with Baker Hughes Scope: Joint development of AI applications for oil and gas Significance: First major strategic alliance Status: Renewed and expanded through June 2028

U.S. Air Force (2019)

Program: Predictive Analytics and Decision Assistant (PANDA) Value: $100 million contract (later expanded to $450 million) Focus: Predictive maintenance for military aircraft Significance: Major federal contract validation

Company Culture Origins

Siebel’s Management Philosophy

From Siebel Systems legacy: - Sales-driven culture - Focus on enterprise sales - Engineering excellence - High-quality product development - Customer success - Deep commitment to outcomes - Operational discipline - Financial rigor

Early C3.ai Culture

• Domain expertise - Deep industry knowledge
• Academic connections - Partnerships with universities
• Government focus - Strong public sector presence
• Long sales cycles - Patient approach to enterprise deals

Historical Context

Why 2009 Was Strategic

• Smart grid investments - Obama administration stimulus
• Big data emergence - Hadoop era beginning
• Cloud computing - AWS gaining enterprise traction
• Early AI/ML - Before deep learning revolution

Siebel’s Return to Software

After selling Siebel Systems to Oracle: - Book published: “Cyber Rules” (2001) - Book published: “Taking Care of eBusiness” (2001) - Philanthropy: Siebel Foundation focus - Personal injury: 2009 elephant attack in Tanzania (serious injuries) - C3.ai founding: Turned focus back to technology

Legacy of the Founding

C3.ai represents: - Second act for Tom Siebel - Successful entrepreneur returning - Enterprise AI pioneer - Early mover in category - Model-driven approach - Differentiated technical architecture - Vertical focus - Industry-specific solutions

The company’s trajectory would be shaped by: - Tom Siebel’s sales expertise and network - The emerging AI/ML market - Enterprise digital transformation trends - Increasing focus on AI applications over platform-only plays

C3.ai - Major Milestones, Expansions & Acquisitions

Major Corporate Milestones

Early Growth Phase (2009-2016)

Expansion and IPO Phase (2017-2021)

Market Challenges and Pivot (2022-2024)

Initial Public Offering (2020)

IPO Details

IPO Market Context

• AI hype peak - Perfect timing for AI-themed IPO
• December 2020 - COVID vaccine optimism; market rally
• Low interest rates - Growth stocks in favor
• Meme stock era - Retail investor enthusiasm

Post-IPO Performance

Strategic Partnerships

Baker Hughes Alliance

Established: 2019 Renewed: 2025 (through June 2028)

Microsoft Strategic Alliance

Expanded: 2024-2025

Results (FY25): - 28 agreements in Q4 FY25 - 100+ joint customer meetings at C3 Transform - 16 joint events - Sales cycles shortened 20%

Amazon Web Services (AWS)

Partnership: Expanded 2024

• C3 AI applications on AWS Marketplace
• Joint go-to-market
• Co-selling activities

Google Cloud

Partnership: 2024

• Similar arrangement to AWS
• Joint customer development

McKinsey & Company / QuantumBlack

Established: 2025

PwC Alliance

Established: 2025

• Strategic alliance for financial services, manufacturing, utilities
• Combines C3 AI platform with PwC advisory

Other Partnerships

Federal Business Growth

U.S. Air Force PANDA Program

Other Federal Contracts

FY25 Federal Statistics: - 51 agreements closed - 20% of total bookings

Product Evolution

From Platform to Applications

C3 Generative AI Launch (2023)

Capabilities: - Domain-specific generative AI - Enterprise data integration - Secure, private deployment

Growth: - FY25: 66 initial production deployments - 16 industries - 100%+ revenue growth in segment

Acquisitions

C3.ai has made minimal acquisitions compared to peers, focusing on organic development:

Strategy: Build rather than buy; Siebel’s preference for organic growth

Customer Growth

Customer Count Progression

Notable Customers

Financial Milestones

Revenue Growth

Profitability Journey

Competitive Positioning

vs. Palantir

vs. Snowflake

vs. Databricks

Strategic Shifts

2023: Consumption Pricing

Change: Moved from subscription to consumption-based pricing Rationale: Align with cloud vendors; reduce friction Impact: Initial revenue headwinds; now showing growth

2024: Partner-Centric Growth

Strategy: 73% of agreements through partners Goal: Scale without proportional sales hiring Results: Partner bookings up 419% YoY in Q4

2025: Agentic AI Focus

Claim: “We invented the model-driven agentic Enterprise AI platform” Patent: U.S. Patent for agentic generative AI awarded Market: Emerging category; first-mover positioning

C3.ai - Products, Services & Technology Innovations

Core Product Portfolio

C3 AI Platform

The foundational technology for all C3.ai offerings:

Architecture: - Model-driven - Abstract data/application models - Cloud-native - AWS, Azure, Google Cloud, on-premise - Microservices - Containerized deployment - API-first - RESTful APIs throughout

C3 AI Applications

Pre-built, industry-specific applications:

C3 Generative AI

Domain-specific generative AI offerings:

Key Capabilities: - Omni-Modal Parsing - Extract content from any format - Dynamic Planning Agent - Multi-step reasoning - Easy Agent Authoring - Rapid agent development - Custom Visualizations - Natural language to charts

C3 AI Agentic AI Platform

Patent: Awarded U.S. patent for agentic AI (filed Dec 2022)

Capabilities: - Multi-agent collaboration - Autonomous task execution - Tool integration - Enterprise system connectivity

Industry Solutions

Oil and Gas

Notable Customers: Shell, ExxonMobil, Baker Hughes, Enel

Manufacturing

Notable Customers: 3M, Cargill, Koch Industries, GSK

Financial Services

Notable Customers: Bank of America, Fannie Mae, BNY Mellon

Defense and Intelligence

Notable Customers: U.S. Air Force, U.S. Navy, Missile Defense Agency

Healthcare

Notable Customers: Mayo Clinic, Stanford Health Care

Technology Innovations

Model-Driven Architecture

C3.ai’s core technical differentiation:

Concept: - Define models once (data, analytics, application) - Auto-generate code and infrastructure - Rapid application development - Consistent enterprise scale

Benefits: - 10x faster development vs. coding - Consistent architecture - Easy maintenance - Enterprise scalability

Data Integration

Supported Systems: - ERP: SAP, Oracle, Workday - CRM: Salesforce, Microsoft Dynamics - Databases: Oracle, SQL Server, PostgreSQL, Snowflake - Cloud: AWS, Azure, Google Cloud - IoT: Industrial sensors, SCADA

Machine Learning

Integration: - TensorFlow - PyTorch - scikit-learn - Custom algorithms

Security Features

Recent Innovations (2024-2025)

Agentic AI Breakthroughs

Dynamic Planning Agent: - Multi-step reasoning - Tool orchestration - Goal-oriented execution

Multi-Agent Collaboration: - Agent-to-agent communication - Task decomposition - Coordinated execution

C3 Generative AI Enhancements

Customer Success Stories

U.S. Air Force PANDA

• Aircraft monitored: 100s across fleet
• Data sources: Flight, maintenance, supply
• Results: Reduced downtime, improved readiness
• Scale: $450M contract ceiling

USC Shoah Foundation

• Use case: Survivor testimony indexing
• Scale: 30,000 testimonies
• Time saved: 10 years of manual effort
• Cost saved: $33 million

GSK Demand Forecasting

• Scope: Global supply chain
• Results: Improved forecasting accuracy
• Impact: Manufacturing optimization

Research and Development

R&D Investment

Note: High R&D ratio due to investment phase

Patent Portfolio

• U.S. patents: 100+
• International patents: Additional filings
• Key patent: Agentic generative AI (awarded)
• Focus areas: Model-driven architecture, AI applications

Research Partnerships

Competitive Differentiation

vs. General-Purpose Cloud AI

vs. Data Science Platforms

vs. Vertical SaaS

Product Strategy

Turnkey vs. Platform Tension

C3.ai navigates between: - Pre-built applications - Faster time-to-value - Custom development - Platform capability demonstration - Partnership model - Scaling through system integrators

Consumption Pricing Impact

The shift to consumption pricing (2023): - Lower barrier to entry - Aligns with cloud economics - Revenue recognition changes - Customer commitment flexibility

Future Roadmap

FY2026 Priorities

1. Agentic AI scaling - Production deployments
2. Partner ecosystem - McKinsey, PwC expansion
3. Vertical expansion - New industry applications
4. Generative AI monetization - Revenue growth
5. Federal expansion - Defense and intelligence growth

C3.ai - Financial Performance

Stock Information

Annual Financial Performance

Revenue History

Fiscal year ends April 30

Fiscal Year 2025 Financial Highlights

• Revenue: $389.1 million (+25% YoY)
• Subscription Revenue: $327.6 million (+18% YoY)
• Subscription % of Total: 84%
• GAAP Gross Profit: $235.9 million (61% margin)
• Non-GAAP Gross Profit: $270.6 million (70% margin)
• GAAP Net Loss: $(2.24) per share
• Non-GAAP Net Loss: $(0.41) per share
• Cash & Investments: $742.7 million

Quarterly Performance (Q4 FY2025)

Revenue Composition

By Type

Professional Services Breakdown

Profitability Metrics

Margin Analysis (FY2025)

Path to Profitability

C3.ai remains in investment mode: - Heavy R&D spending ($271M in FY2025) - Sales and marketing investment - Focus on growth over near-term profitability - Target: Profitable in coming years

Balance Sheet

Assets (April 30, 2025)

Liabilities

Key Metrics

Cash Flow

FY2025 Cash Flow Summary

Cash Burn Analysis

Stock Performance

Price History

Trading Characteristics

• Volatility: High (beta ~2.0)
• Volume: Active retail interest
• Short interest: Historically elevated
• Options activity: Significant

Customer Metrics

Customer Growth

Customer Concentration

Guidance and Outlook

FY2026 Guidance

Implied growth: 15-25% year-over-year

Long-Term Targets

Comparison with Peers

Valuation Metrics (February 2026)

Note: C3.ai trades at significant discount to peers

Growth Comparison

Growth rates comparable; valuation multiples divergent

Investment Considerations

Bull Case

1. AI tailwinds - Enterprise AI adoption accelerating
2. Partner momentum - 73% of deals through partners
3. Federal business - $450M Air Force contract; sticky revenue
4. Strong cash - 5+ years runway
5. Founder pedigree - Tom Siebel’s track record

Bear Case

1. Profitability elusive - 6+ years of losses
2. Customer concentration - Heavy reliance on Baker Hughes
3. Competition - Cloud vendors, Palantir, emerging players
4. Sales execution - Turnover and reorganization
5. Valuation compression - Trading below IPO price

Analyst Coverage

Rating Distribution (Typical)

Price Target Range

Note: Wide dispersion reflects uncertainty

C3.ai - Leadership & Corporate Culture

Executive Leadership

Current Leadership Team (2025)

CEO Transition

Stephen Ehikian (CEO since September 2025)

Background

• Previous Roles:
• Built and sold two companies to Salesforce
• Senior executive at Salesforce
• Enterprise software veteran

Taking the Reins

Announcement: August 2025 Effective: September 1, 2025

Context: - Tom Siebel stepped down due to health (autoimmune disease) - Siebel remains Chairman - Ehikian tasked with accelerating growth to profitability

Initial Statement:

“C3 AI is one of the most important companies in the AI landscape and enterprise software, with a platform and applications that are unmatched. I am confident that we will be able to capture an increasing share of the immense market opportunity in Enterprise AI.”

Former CEO: Thomas M. Siebel (2009-2025)

Leadership Style

Siebel’s management approach at C3.ai:

1. Visionary Sales Leadership
2. Personal involvement in major deals
3. Strong customer relationships

4. Industry evangelism

5. Engineering Focus

6. Technical depth in decision-making
7. Patent-driven innovation

8. Architecture-first approach

9. Long-term Perspective

10. Patient capital allocation
11. Willingness to invest through losses

12. Platform over quick wins

13. Controversial Communication

14. Outspoken on earnings calls
15. Criticized sales team publicly
16. Strong opinions on competition

Health Challenges (2025)

• Diagnosis: Autoimmune disease (early 2025)
• Impact: Significant visual impairment
• Response: Continued working with accommodations
• Outcome: Decision to step down as CEO

August 2025 Statement

On disappointing preliminary results:

“Sales results during the quarter were completely unacceptable…attributed to the ‘disruptive effect’ of the reorganization, as well as his ongoing health issues.”

Corporate Culture

Siebel’s Cultural Influence

From Siebel Systems legacy and C3.ai founding:

1. Sales-Driven Culture

• Quota achievement paramount
• Executive involvement in deals
• Long sales cycles accepted
• Customer success obsession

2. Technical Excellence

• Engineering-centric decision making
• Architecture as competitive advantage
• Patent-driven innovation
• Academic rigor

3. Customer Intimacy

• Deep vertical expertise
• Outcome-based relationships
• Executive sponsorship model
• Reference customer focus

Organizational Structure

Functional Organization

Sales Organization Evolution

2024 Restructuring: - Global sales reorganization - Partner enablement focus - Industry vertical alignment - Federal division expansion

Challenges: - Sales turnover - Disruption during transition - Quota attainment issues - Q1 FY25 underperformance

Employee Relations

Workforce Statistics (2025)

Geographic Distribution

Compensation Philosophy

• Competitive base salaries
• Significant equity participation
• Performance-based bonuses
• Long-term incentive focus

Culture Challenges

Reported Issues: - High turnover in sales organization - Pressure to perform - Quota-driven stress - Remote work - Post-COVID transitions - Stock price impact - Employee morale

Decision Making

Strategic Decisions

Operating Cadence

• Weekly: Sales pipeline reviews
• Monthly: Operating reviews
• Quarterly: Board meetings, earnings
• Annual: Strategic planning, C3 Transform

Board of Directors

Board Composition

Board Committees

• Audit Committee
• Compensation Committee
• Nominating & Governance

Communication Culture

Investor Communications

Tom Siebel’s Style: - Direct and opinionated - Long-term focus messaging - Competitive commentary - Detailed technical explanations

Notable Moments: - August 2025: “Completely unacceptable” sales results - Criticism of competitors (Palantir comparisons) - Patent ownership claims

Internal Communications

• All-hands meetings - Regular company updates
• C3 Transform - Annual user conference
• Siebel’s influence - Strong founder presence

Evolution Under New Leadership

Expected Changes (Ehikian Era)

1. Operational discipline - Salesforce-style execution
2. Partner scaling - Accelerate partner-led growth
3. Sales productivity - Improve quota attainment
4. Profitability focus - Path to cash flow positive
5. Culture evolution - From founder-led to professional management

Salesforce Influence

Ehikian’s background suggests: - Process rigor - Salesforce operational excellence - Partner ecosystem - AppExchange model - Land-and-expand - Growth strategy - Customer success - Retention focus

Governance

Shareholder Structure

Voting Control

• Dual-class structure (historically)
• Siebel maintains significant influence
• Board independence requirements

Leadership Legacy

Tom Siebel’s C3.ai Legacy

Achievements: - Built enterprise AI category - Created model-driven architecture - Secured major federal contracts - Took company public - Established strategic partnerships

Challenges: - Sustained profitability elusive - Sales execution inconsistency - Stock price underperformance - CEO transition circumstances

Future Under Ehikian

Key questions: - Can he accelerate growth? - Will culture evolve appropriately? - Can profitability be achieved? - How will Siebel’s involvement change?

C3.ai - Corporate Social Responsibility & Philanthropy

CSR Approach

C3.ai’s corporate social responsibility focuses on: 1. AI for Good - Applying AI to societal challenges 2. Education - STEM and AI literacy 3. Environmental Sustainability - Climate and energy solutions 4. Community Engagement - Local community support

C3.ai Global Initiatives

AI for Climate and Sustainability

C3.ai Digital Transformation Institute

Established: 2020 Partnership: C3.ai, Microsoft, leading universities Funding: $100+ million commitment

Mission: Accelerate AI research for societal benefit

Research Grants Program

• Grant size: $100,000 - $250,000
• Duration: 12 months
• Recipients: University researchers
• Topics: Climate, energy, health, security

Notable Universities: - MIT - Stanford - UC Berkeley - Carnegie Mellon - Princeton

COVID-19 Response (2020-2022)

C3.ai COVID-19 Data Lake

Launched: April 2020 Purpose: Free data resource for pandemic research

Features: - Unified COVID-19 data repository - Epidemiological data - Healthcare system data - Economic impact data - Free access to researchers worldwide

Impact: - Supported hundreds of research projects - Enabled predictive modeling - Informed policy decisions - Demonstrated AI for social good

Research Grants

• $3.3 million in COVID-19 research grants
• 21 research projects funded
• Focus: Modeling, prediction, response optimization

Education Initiatives

University Partnerships

Student Engagement

• Internships - Summer programs
• Hackathons - AI competitions
• Curriculum - Guest lectures, case studies
• Mentorship - Employee volunteer program

C3.ai Academy

Internal and external training: - Employee development - Technical and professional - Customer training - Platform certification - Partner enablement - Technical accreditation

Environmental Sustainability

Product Impact

C3.ai applications directly support sustainability:

Customer Sustainability Outcomes

Energy Sector: - Optimized renewable energy integration - Reduced fossil fuel consumption - Improved grid efficiency

Manufacturing: - Reduced waste through predictive maintenance - Optimized resource utilization - Lower emissions through efficiency

Carbon Footprint

C3.ai’s own operations: - Cloud-based - Efficient infrastructure - Remote work - Reduced commute emissions - Small physical footprint - Limited facilities

Community Engagement

Local Community Support

Employee Volunteering

• Paid volunteer time - Company-supported
• Skills-based volunteering - Technical expertise
• Pro bono projects - Nonprofit support

Matching Gift Program

• Match ratio: 1:1
• Annual limit: Employee donations matched
• Eligible organizations: 501(c)(3) nonprofits

Diversity and Inclusion

Workforce Diversity

Inclusive Culture

• Unconscious bias training
• Inclusive hiring practices
• Accessibility - Workplace and product
• Mental health support

Diversity Metrics (Approximate)

Ethical AI Development

AI Ethics Principles

C3.ai’s commitment to responsible AI:

Responsible AI Practices

• Model validation - Testing for bias
• Data governance - Ethical data use
• Human-in-the-loop - Decision oversight
• Documentation - Model explainability

Nonprofit and NGO Partnerships

Technology Donations

• Software licenses - Nonprofit pricing
• Pro bono services - Implementation support
• Training - Capacity building

Strategic Partnerships

Transparency and Reporting

ESG Reporting

C3.ai provides: - Sustainability disclosures - Environmental impact - Diversity reports - Workforce composition - Ethics policies - AI and business conduct

Governance

• Board oversight - ESG considerations
• Ethics committee - AI ethics review
• Compliance - Regulatory requirements

Comparison with Peers

CSR Investment (% of Revenue)

C3.ai’s Digital Transformation Institute represents significant commitment relative to company size

Criticisms and Challenges

Limited Disclosure

• Less detailed ESG reporting than larger peers
• Limited community investment data
• Smaller scale than tech giants

Focus Areas

Critiques include: - CSR tied closely to business interests - Limited grassroots community engagement - Small absolute investment vs. large companies

Future Commitments

C3.ai has committed to: - Continued Digital Transformation Institute funding - Expanded university partnerships - Enhanced diversity initiatives - Stronger ESG reporting - AI for Good program expansion

C3.ai - Legacy, Impact & Challenges

Industry Impact

Pioneering Enterprise AI

C3.ai’s contributions to the enterprise AI market:

Market Category Creation

C3.ai claims to have invented the Enterprise AI category: - First company focused exclusively on enterprise AI - Predated current AI hype cycle - Established AI as enterprise software category - Influenced competitor positioning

Technology Influence

Model-Driven Architecture: - Influenced enterprise AI platform design - Demonstrated value of abstraction layers - Showed scalability of declarative models - Patented core innovations

Industry-Specific Applications: - Proved vertical AI application value - Influenced competitor product strategies - Established playbook for enterprise AI

Market Position

Competitive Landscape (2025)

Positioning Challenges

C3.ai occupies a challenging market position: - Smaller than pure-play competitors (Palantir) - Narrower than cloud vendors (AWS, Azure, GCP AI) - More expensive than open source - Less proven than established vendors

Economic Impact

Direct Impact

• Employment: ~1,100 high-skilled jobs
• Customer value: Billions in operational savings
• Tax contribution: State and federal taxes
• Innovation: Patent portfolio

Customer Impact

Energy Sector: - Optimized oil and gas operations - Reduced emissions through efficiency - Improved renewable integration

Manufacturing: - Predictive maintenance savings - Supply chain optimization - Quality improvements

Federal: - Military readiness improvements - Logistics optimization - National security applications

Controversies and Challenges

Stock Price Underperformance

IPO to Present: - IPO price: $42 (Dec 2020) - All-time high: $183.90 (Dec 2020) - Current: ~$25-35 (2025) - Performance: Down ~30% from IPO

Reasons for Underperformance: - Revenue growth slower than expected - Profitability remains elusive - Sales execution challenges - Competition from larger players - Shift to consumption pricing

Sales Execution Issues

2024-2025 Challenges: - Q1 FY25 revenue miss - Sales reorganization disruption - CEO health issues - “Completely unacceptable” results (Siebel)

Turnover: - Multiple sales leadership changes - Quota attainment issues - Customer concentration risk

Competition Intensity

Cloud Vendor Threat: - AWS SageMaker, Azure ML, Google Vertex AI - Bundled pricing advantages - Ecosystem integration - Marketing budgets

Palantir Competition: - Similar government focus - Larger scale and resources - Gotham vs. C3 AI Platform - AIP (AI Platform) launch

Emerging Players: - Vertical AI startups - Open-source alternatives - LLM-native companies

Customer Concentration

Risks: - Baker Hughes: ~15% of revenue - Top 3 customers: ~30% of revenue - Loss of major customer would be significant

Pricing Model Transition

2023 Change: Subscription to consumption - Initial revenue headwinds - Customer confusion - Reporting complexity - Long-term benefits unclear

Historical Significance

Tom Siebel’s Legacy

C3.ai represents Siebel’s second major software company:

Siebel Systems (1993-2006): - Pioneered CRM category - Fastest-growing software company of era - $5.85B sale to Oracle - Iconic enterprise software success

C3.ai (2009-present): - Pioneered enterprise AI - Public company (2020) - Ongoing growth challenges - Unfinished legacy

Comparison: Siebel Systems vs. C3.ai

First-Mover Disadvantage?

C3.ai may have been too early: - Founded 2009 (before AI hype) - Market education required - Customer readiness limited - Technology maturity issues

Future Outlook

Growth Opportunities

1. AI boom tailwind - Enterprise AI adoption accelerating
2. Partner ecosystem - Scaling through partners
3. Federal expansion - Defense and intelligence growth
4. Generative AI - New product category
5. International - Global expansion

Strategic Challenges

1. Profitability - Path to sustainable business model
2. Competition - Defending against larger players
3. Sales execution - Improving consistency
4. Customer diversification - Reducing concentration
5. Product differentiation - Maintaining edge

CEO Transition Impact

Stephen Ehikian’s challenges: - Turn around sales organization - Accelerate growth - Achieve profitability - Navigate competitive landscape - Define post-Siebel culture

Legacy Assessment

Positive Contributions

1. Category creation - Established enterprise AI
2. Technical innovation - Model-driven architecture
3. Federal validation - Government sector credibility
4. AI research - Digital Transformation Institute
5. Customer value - Documented ROI

Disappointments

1. Stock performance - Significant decline from highs
2. Profitability - Continued losses after 16 years
3. Scale - Smaller than envisioned
4. Sales execution - Inconsistent performance
5. Market share - Limited vs. competitors

Historical Position

C3.ai will be remembered as: - An enterprise AI pioneer - Early mover, category creator - A study in market timing - Too early for AI boom - Tom Siebel’s second act - Ambitious but incomplete - A survivor - Navigating competitive challenges - Work in progress - Future depends on new leadership

Conclusion

Current State (2025)

C3.ai is at an inflection point: - New CEO with Salesforce background - Strong cash position ($743M) - Growing revenue (25% YoY) - Challenging profitability path - Intense competition

Possible Futures

Ultimate Legacy

C3.ai’s ultimate legacy depends on: - Next 2-3 years under new leadership - Profitability achievement - Competitive positioning - Market category development

Whether C3.ai becomes: - A success story - Siebel’s second triumph - A cautionary tale - First-mover disadvantage - An acquisition - Technology absorbed by larger player - A survivor - Niche player in large market

Will be determined by execution under new leadership and market dynamics in the rapidly evolving enterprise AI landscape.