Every AI success story starts with a single decision: to move beyond experimentation and commit to real-world impact. But moving from idea to enterprise-scale deployment isn’t just about algorithms – it’s about laying the right groundwork.
In the first part of this series, we explored three ways to lay the foundation for AI success: committing to change, identifying a key business problem, and updating your development plan. Now, we’ll dive into the final two steps from the SAS AI Starter Kit – seizing your data and scaling responsibly – to help you move from experimentation to enterprise-wide impact.
Step 4: Seize the data
Whether you’re in financial services, pharmaceuticals or the public sector, your AI models are only as good as the data they’re trained on. For example:
- A bank needs clean transaction data to detect fraud.
- A manufacturer needs sensor data to predict equipment failures.
- A health agency needs accurate patient data to forecast disease outbreaks.
However, it’s important to remember that AI is data-dependent. Because the vast majority of organizations have an IT infrastructure that grew organically over the course of years – or even decades – data can be siloed, incomplete or simply incorrect. Bad data spells disaster for AI use.
Unreliable data can lead to poor AI model performance, inaccurate predictions and, ultimately, misguided business decisions. Bad data feeds can corrupt AI algorithms, causing them to malfunction, misinterpret information or fail to detect critical issues. This can result in financial losses, reputational damage and compliance risks for organizations. To avoid these pitfalls, ensure robust data validation and continuous monitoring processes are in place.
So, how do you prepare?
- Focus on access and quality: Your data doesn’t need to be perfect, but it must be meaningful and accessible.
- Enhance existing data governance efforts: Effective data governance is essential for maintaining data quality. Organizations should focus on access and quality, ensuring that data is meaningful and accessible.
- Build a data pipeline: Use tools like SAS® Viya® and Model Studio to automate data preparation and ensure consistency.
- Generate synthetic data: If you lack sufficient data, SAS® Data Maker offers point-and-click synthetic data generation to simulate real-world scenarios.
Explore how SAS Data Maker can help you augment or generate data quickly
Step 5: Go slow to go fast – test, learn, scale
AI adoption doesn’t require a massive leap. In fact, the most successful organizations start small, testing low-risk, high-impact use cases before scaling.
You’re likely already using AI in some form – whether it’s a chatbot, a recommendation engine, or automated document processing. The key is to evaluate your current analytics capabilities and identify areas where AI can enhance them.
For example:
- Pharmaceutical companies can use AI to accelerate clinical trials.
- Public sector agencies can use natural language processing (NLP) to analyze citizen feedback.
- Insurers like CNseg used machine learning to detect fraudulent claims, achieving a 67% increase in fraud detection.
SAS offers a comprehensive suite of data and AI solutions designed to help organizations harness the power of their data for better decision-making and improved business outcomes. With SAS Viya, organizations use advanced analytics, machine learning, and real-time decisioning to address evolving threats and enhance operational performance.
Once your assessment is complete, you can begin testing the waters. Remember, you don’t have to push the accelerator to the floor. With machine learning, computer vision, natural language processing, or other forms of AI you can shorten the new policy acquisition process, settle claims, or even fight fraud.
Build a responsible AI strategy
Scaling AI isn’t just about technology – it’s about governance. SAS offers a proven AI governance maturity model to help organizations manage risk, ensure compliance and build trust.
Learn more about how SAS provides a governance structure for AI
Bonus: 5 ways to prepare for an AI future today
- Take the free Generative AI Using SAS® course: A practical introduction to GenAI for professionals in any industry.
- Assess your AI governance maturity using the AI Governance Map: Use SAS tools to evaluate your data quality and readiness.
- Start with a use case: Focus on one high-impact problem to solve.
- Upskill your team: Enroll in the free AI Literacy course to build foundational knowledge.
- Partner with experts: SAS has over 50 years of experience in analytics and can help guide your journey.
Your AI journey starts now
AI is not a destination – it’s a journey. And like any journey, it starts with a single step. With SAS Viya, you have a trusted platform that combines data management, model development, and responsible deployment – all in one place.
Whether you’re looking to reduce costs, improve decision-making, or enhance customer experiences, SAS Viya can help you get there – safely, strategically and at scale.
Want to see what SAS can really do?
Get a free 14-day trial of SAS Viya and test it for yourself
