Building an AI Organization Competency
Business Problem
Our teams experiment with AI, but we lack a cohesive strategy, scalable skills, and responsible governance to embed AI in our products, operations, and decision-making.
Business Outcomes
- Enhanced competitiveness by leveraging AI to personalize customer experiences and uncover new revenue streams.
- Greater workforce productivity by augmenting employee capabilities with AI tools.
- Accelerated innovation cycles that shorten time-to-market for new products and services.
- Increased operational efficiency by using AI to optimize workflows, reduce manual effort, and generate deeper insights from organizational data to drive smarter, faster decisions.
Why is Building an AI Organization Competency important?
Becoming an AI organization is essential for companies seeking to remain competitive, innovative, and resilient in a rapidly evolving digital economy. As AI reshapes how work is done, decisions are made, and value is delivered, organizations that embed AI across their operations, tools, and customer offerings position themselves to lead rather than lag.
An AI organization uses AI not only to enhance internal productivity—automating routine tasks, surfacing insights, and accelerating decision-making—but also to enrich its products and services. This dual focus drives both operational efficiency and market differentiation. With AI embedded into customer experiences, companies can offer smarter, more adaptive solutions and unlock new business models, setting themselves apart from slower-moving competitors.
Achieving this change requires more than deploying a few AI tools. It begins with executive alignment and a clear AI vision linked to strategic goals. Success depends on a modern data infrastructure, robust governance, and scalable technology platforms that allow AI to be deployed responsibly across the enterprise. Workforce readiness is equally critical. Employees must be equipped to use AI tools confidently and ethically, and leaders must foster a culture of experimentation, learning, and trust in augmentation over automation.
In parallel, the company’s approach to product development must evolve. AI needs to be thoughtfully embedded in offerings, with a strong emphasis on user value, transparency, and safety. Responsible AI practices—covering fairness, explainability, data privacy, and model monitoring—must be integral from the start.
Ultimately, becoming an AI organization is a capability-building journey. It demands investment, leadership commitment, and a mindset shift across the workforce. But for companies that get it right, the reward is not just greater efficiency—it’s the ability to continually innovate, adapt, and lead in a world increasingly shaped by intelligent systems.
Which roles would benefit from mastering this competency?
The very nature of this competency, specifically the attribute of creating an AI-augmented workforce, means that every role in an organization can benefit. That means that the most relevant AI tools for each role are approved, available, and supported by all areas of leadership. It also means that employees receive training on how to maximize the benefit of these tools and that the approved tools have passed a rigorous review, testing, and approval process to ensure that they adhere to the organization’s Responsible AI policies and practices.
Learning about the Building an AI Organization Competency
The following resources are suitable for beginning your learning journey on the Becoming an AI Organization competency:
Introduction to Artificial Intelligence (AI)
Artificial Intelligence (AI) has existed long before the introduction of generative AI tools such as ChatGPT. This article provides a basic instruction to this technology.
Artificial Intelligence (AI) in SAFe
Artificial Intelligence (AI) is a term used to describe a wide range of smart machines capable of performing tasks that typically require human intelligence. AI can be applied at all levels of SAFe to increase productivity, build intelligent customer solutions, automate value stream activities, and improve customer insights.
AI Augmented Workforce: A Leader’s Guide to Unleashing Human Potential
The power of AI in an organization is realized when this technology is made available to all employees so they can experience increased productivity, unlock innovation, accelerate flow, improve quality, and reduce repetitive tasks. This article shows you how.
Responsible AI
The power of AI in an organization is realized when this technology is made available to all employees so they can experience increased productivity, unlock innovation, accelerate flow, improve quality, and reduce repetitive tasks. This article shows you how.
Keynote AI and the Future of Work
Organizations using AI can unleash human potential, shaping the future of business. Dr. Steve Mayner, VP of the SAFe Framework Team, and Dr. Mik Kersten, CIO of Planview and author of Project to Product, discuss in this video how AI is changing how people work. They provide specific examples of how AI is helping all roles in SAFe from individual developers all the way to portfolio leaders.
Applying the Building an AI Organization Competency
Here are some key initial considerations as you begin to apply your knowledge:
- Set a clear AI vision aligned with business goals – Define how AI will create value across operations and offerings, with strong executive alignment.
- Establish data and technology foundations – Build reliable data infrastructure, ensure data quality, and adopt scalable AI platforms.
- Start with high-impact use cases – Identify and build initial AI capabilities that address real business problems and demonstrate measurable value.
- Develop talent and responsible AI practices – Upskill teams, hire strategically and embed ethical guidelines into all AI efforts.
- Scale and evolve with a culture of innovation – Expand successful pilots, encourage experimentation, and continuously refine AI strategies.
The following resources are suitable for developing the skills for applying the Building an AI Organization competency:
Building, Operating, and Scaling AI-Enabled Solutions with SAFe
This webinar will examine the impacts of AI solution development on people, processes, and technology.
How SPCs Can Use SAFe CoPilot – SAI Webinar
In this webinar SPC Jason Flynn covers tips and tricks for using SAFe CoPilot as an SPC to help in day-to-day coaching and work.
Mastering the Building an AI Organization Competency
Once the foundations of using AI in your organization have been established, the following tips can help AI become integral to every aspect of the enterprise:
- Adopt AI-Driven decision frameworks – Integrate AI insights into strategic and operational decision-making processes enterprise-wide.
- Continuously optimize AI Models in production – Monitor, retrain, and fine-tune models regularly to maintain accuracy, relevance, and performance.
- Enable cross-functional AI Collaboration – Create multidisciplinary teams that blend domain expertise, data science, and engineering to accelerate innovation.
- Embed AI into core products and services – Move beyond isolated features to make AI a fundamental layer of customer value delivery.
- Institutionalize Responsible AI at scale – Operationalize governance with automated tools for bias detection, explainability, and compliance across all AI workflows.
Achieving Responsible AI – SAFe Micro-credential
This course will make you stand out as a leader in implementing responsible AI by providing hands-on experience and practical skills that ensure your AI projects are transparent, accountable, and aligned with human values.
Becoming an AI-Native Finance Company: A Transformation Story
Global FinanceCo had dominated the financial services sector for generations. Known for its stability and scale, the firm managed trillions in assets and served millions globally. But by 2024, cracks had started to show. Nimble fintech startups were using AI to offer hyper-personalized investment advice, instant loan approvals, and real-time fraud detection. Global FinanceCo, weighed down by legacy systems and siloed operations, struggled to keep pace with rising customer expectations and digital competitors.
CEO Natalia Roma recognized the threat wasn’t technological—it was cultural and structural. Becoming an AI organization meant more than adopting new tools. It required redefining how decisions were made, products were designed, and teams operated. To drive the transformation, she established a company-wide AI Enablement Office composed of leaders from analytics, IT, compliance, customer experience, and business lines.
The first initiative targeted internal workflows. Generative AI copilots were deployed in financial advisory, regulatory reporting, and customer onboarding. Advisors used AI to simulate market scenarios, generate client-ready portfolio briefs, and personalize outreach based on behavioral insights. Operations teams automated the creation of compliance reports, reducing what once took days to mere minutes—while maintaining auditability.
Meanwhile, customer-facing offerings evolved. AI-driven chat agents now handle over 70% of routine inquiries, improving response time and freeing up staff for complex cases. Loan underwriting used agentic AI models that analyzed thousands of data points in real-time, enabling same-day approvals with lower default risk. AI was embedded in wealth management tools, giving clients dynamic investment guidance tailored to life events, goals, and market trends.
Leadership practices matured in tandem. AI-curated dashboards provided executives with leading indicators on market sentiment, operational bottlenecks, and emerging client needs. Strategy sessions shifted from backward-looking metrics to forward-facing insights, with leaders being trained to interrogate AI outputs and recognize model limitations. AI fluency became a baseline expectation at every level of leadership.
Eighteen months into the transformation, the impact was clear. Operational costs dropped 22%. Customer satisfaction hit all-time highs. A digital-first wealth product launched exclusively for Gen Z clients gained over 500,000 users in its first year. Most importantly, Global FinanceCo had redefined itself—not just using AI, but running on it.
By reengineering how it worked, decided, and delivered value, Global FinanceCo demonstrated that even the most established financial institutions can become AI-native—and in doing so, lead the next era of finance.
Continuing your journey through the Leadership and Culture Discipline
Leading Change
This competency helps leaders use techniques that facilitate healthy changes in the organization.
Creating a Learning Organization
This competency helps the organization cultivate learning and experimentation more deeply across all areas.
Last Update: 13 February 2026