Article
AI readiness unlocked: Oracle’s blueprint for enterprise transformation
Jul 30, 2025 · Authored by Dave DuVarney, Daniel Jensen
As artificial intelligence (AI) transforms the business landscape, corporations face a vital question: How do we prepare for and successfully implement AI technologies? The answer lies not in rushing to adopt the latest AI tools, but in understanding and building organizational readiness across multiple dimensions.
With AI-powered capabilities already deployed across their application suite and a comprehensive cloud infrastructure supporting major language models, Oracle is demonstrating how enterprise AI should work in practice. Recent discussions in an AI webinar with Baker Tilly’s Dave DuVarney, Principal; Daniel Jensen, Senior Manager and Oracle’s Jody Clayton, Group Vice President, revealed that most organizations recognize AI as essential for future competitiveness, but many struggle with where to begin. The key is establishing a structured framework that addresses the fundamental building blocks of AI success.
The five dimensions of AI readiness
The foundation of AI readiness begins with identifying the right use cases. The most successful organizations approach this as an innovation process, generating multiple ideas before narrowing focus to high-impact, manageable projects. Businesses must balance three critical factors:
- Organization value: What business problems will AI solve?
- Complexity: How difficult will implementation be?
- Strategic impact: Which initiatives will deliver meaningful results?
Quality data remains the cornerstone of effective AI implementation. Without solid data foundations, even the most sophisticated AI tools will produce unreliable results. Organizations should evaluate both structured and unstructured data assets, ensuring:
- Strong data governance frameworks
- Well-categorized and organized information
- Clean, reliable data sources
- Proper data architecture for AI applications
Modern AI implementations require robust technical infrastructure with appropriate security measures. Evaluating infrastructure’s ability better supports AI initiatives while maintaining security standards and regulatory compliance. Key considerations include:
- Scalable computing resources for AI workloads
- Secure data handling and privacy protection
- Integration capabilities with existing systems
- Compliance with regulatory requirements
AI adoption can introduce new categories of risk that require careful management. Many businesses extend their existing data privacy policies to cover AI governance, addressing both opportunities and risks. It’s crucial to have:
- Clear AI governance policies
- Risk assessment frameworks specific to AI use cases
- Data privacy protections
- Compliance with emerging AI regulations
Perhaps the most important dimension, successful AI adoption requires a fundamentally different approach than traditional technology implementations. Instead of mandating usage, organizations must:
- Identify and empower AI enthusiasts throughout the organization
- Create communities for sharing experiences and best practices
- Develop evangelization strategies
- Implement detailed learning and change processes
Oracle’s enterprise AI
Oracle’s approach to enterprise AI represents a fundamental departure from traditional software strategies. Rather than offering AI as a separate product or service, Oracle has built integrated AI capabilities directly into its Fusion applications, creating “AI-native” business processes. Oracle Cloud infrastructure hosts all major language model providers. This shared infrastructure ensures optimal performance, security and cost effectiveness for AI workloads. Oracle has built data models that understand business objects and their relationships, enabling AI to provide contextually relevant recommendations and actions.
Security and data sovereignty: Oracle’s AI implementation prioritizes data protection through a few key principles. Organizational data remains within Oracle’s secure environment and is never shared with external language model providers for training purposes. AI agents operate within the same permission structures as human users, ensuring that AI cannot access data or perform actions beyond a user’s authorized space. Additionally, Oracle’s AI capabilities are built to comply with emerging AI regulations, including the EU AI Act and various regional requirements.
Human in-the-loop design: Oracle’s AI maintains human control over all business decisions. AI provides recommendations and assistance rather than making autonomous decisions and users can retain final approval authority for all AI-generated actions. Additionally, continuous feedback loops improve AI performance over time and allow users to understand AI reasoning.
200+ AI capabilities: AI is embedded across the entire application portfolio, with over 200 capabilities currently available and many more in development. These AI features fall into:
- Generative AI for productivity: Users can generate outcomes and business documents with a single click. The AI uses contextual information from the business processes to create relevant, professional content.
- Predictive analytics for decision making: AI analyzes historical patterns and market conditions, for example, to predict future demand across supply chains and to optimize supplier payment timings.
- Process automation and intelligence: The capabilities streamline tasks like invoice matching, account coding and compliance checks by using AI to reduce manual effort and identify anomalies across operations.
Oracle's Fusion AI Agent Studio
Configuration capabilities
- Modify existing AI agents to match specific business processes
- Add additional approval steps or notifications as needed
- Adjust AI behavior based on organizational preference
Integration options
- Connect existing AI tools and models to Oracle applications
- Leverage custom large language models (LLM) for specialized use cases
Custom agent development
- Build new AI agents for unique business requirements
- Combine multiple AI capabilities into complex workflows
Why “built in, not bolted in” matters
Unlike standalone AI solutions that require complex integrations and custom development, Oracle’s embedded AI provides immediate benefits. Users don’t need to learn new interfaces or change their workflows. The AI capabilities inherit the same security, compliance and governance frameworks that protect critical business data. There’s no need to establish separate security protocols or worry about data leaving secure environments.
With AI embedded across Human Capital Management (HCM), Enterprise Resource Planning (ERP), customer experience and supply chain applications, it provides assistance wherever business value can be created.
Sample AI use cases
Human resources
- Automated goal setting with SMART goal formatting
- Performance review assistance with contextual insights
- Job description generation based on role requirements
- Benefits enrollment guidance through conversational AI
Finance and procurement
- Dynamic payment optimization for supplier discounts
- Automated invoice matching and account coding
- Spend analysis and cost optimization
- Compliance monitoring and exception reporting
Supply chain and logistics
- Demand forecasting with external data integration
- Shipping optimization and delivery prediction
- Inventory management with predictive analytics
- Supplier performance analysis and recommendations
The “crawl, walk, run” strategy for AI adoption
Oracle advises organizations to begin their AI journey with this proven approach:
- Crawl – AI assistance: Start with AI-assisted content creation and recommendations that enhance human productivity without replacing decision-making.
- Walk – Process enhancement: Implement AI capabilities that streamline existing business processes, such as automated invoice matching.
- Run – Agentic AI: Deploy AI agents that can execute complex business processes autonomously while maintaining human oversight and control.
How we can help
As AI reshapes the enterprise landscape, success hinges on building a solid foundation across strategy, data, infrastructure and culture. Oracle’s integrated, secure and human-centric approach to AI offers a blueprint for organizations ready to move from experimentation to enterprise-wide impact.
Watch the full webinar on-demand and discover how Oracle is redefining enterprise AI here.
Baker Tilly is a premier Oracle PartnerNetwork Member, with global capabilities across Oracle’s Cloud platforms, including Analytics, EPM, ERP, HCM and SCM. Mid-market to Fortune 50 clients have looked to Baker Tilly to transform their business with Oracle’s portfolio of enterprise solutions since 2006.
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