Redefining Profitability Through Data Preparation: Reevaluating Return on Investment in the Era of Artificial Intelligence
In the dynamic world of business, staying ahead of the curve is crucial for success. This is especially true when it comes to data management, as the most successful enterprises are readying their data today for tomorrow's opportunities.
Over 90% of enterprise data is unstructured, making it a goldmine of untapped potential. Organizations without a clear data readiness strategy, aligned with business objectives, risk missing out on significant value. Unstructured data readiness is more than just a safeguard; it's a growth strategy.
Sean Nathaniel, CEO of DryvIQ, an Intelligent Data Management Company trusted by over 1,100 organizations worldwide, sheds light on this critical aspect. He outlines the three returns of data readiness as outlined by Gartner: enhanced accuracy and efficiency in AI models, improved trust and risk management, and operational agility and timeliness.
- Enhanced Accuracy and Efficiency in AI Models: AI-ready data is optimized for specific AI use cases, improving model accuracy, reducing bias, and increasing operational efficiency. This allows businesses to scale AI with confidence and obtain more reliable insights that drive growth and better customer outcomes.
- Improved Trust and Risk Management: Data readiness includes governance, metadata for lineage and explainability, and compliance with ethical and regulatory standards. This builds trust in AI decisions, mitigates risks related to bias or intellectual property, and ensures governance frameworks which protect the business and enable sustainable AI deployment.
- Operational Agility and Timeliness: Ready data means it is high-quality (accurate, complete, consistent), fresh (supporting real-time or near-real-time decision making), and contextualized (rich metadata and lineage). This empowers businesses to react rapidly to changing conditions, optimize processes, and support real-time AI-driven actions, thus enhancing competitive advantage and responsiveness.
These three returns of data readiness facilitate business growth by enabling more effective AI, reduced financial and reputational risks, and scalable AI adoption that continuously improves business processes and customer experiences.
In line with Gartner’s 2025 technology priorities, AI agents and AI-ready data are foundational components for organizations aiming for sustainable and scalable AI-driven growth. Rapid AI adoption has transformed data preparation from an IT initiative to an enterprise-wide priority.
Data leaders must translate technical efforts into business outcomes to secure executive buy-in, focusing on insights, alignment with active business initiatives, clear forecasting, demonstrating scalability, and presenting a flexible, scalable data strategy. Companies that invest in scalable, flexible data strategies will be ready not just for AI, but for whatever comes next.
According to Microsoft, more than 80% of organizations expect agents to be moderately or extensively integrated into their AI strategy within the next 12 to 18 months. Generative AI, as per an IDC report, delivers substantial returns, with organizations seeing an average of $3.70 for every dollar spent. For top-performing organizations, that ROI increases to $10.30.
In today's data-driven world, data is now considered a strategic asset, powering AI, automation, and insights that drive growth. Clean, well-classified content enables AI to generate accurate and meaningful insights with the push of a button. A strong data foundation ensures organizational adaptability and innovation, as AI strategies evolve rapidly and new tools, use cases, and regulatory demands emerge.
Businesses are now analyzing and organizing data to unlock value and drive measurable outcomes. When content is organized and AI-ready, employees can spend less time sifting through data and more time solving problems. Data readiness is an ongoing, strategic initiative that enables speed, agility, and innovation, as enterprise data volumes grow and business priorities shift.
In conclusion, data readiness is not just a necessity but a competitive advantage in the AI era. It empowers businesses to make more informed decisions, manage risks effectively, and stay agile in an ever-changing business landscape. As Forbes Technology Council rightly puts it, data readiness is the key to unlocking the full potential of AI and driving sustainable growth.
- Sean Nathaniel, the CEO of DryvIQ, emphasizes that data readiness is crucial for businesses, noting Gartner's three returns: improved efficiency and precision in AI models, enhanced trust and risk management, and operational agility and timeliness.
- In the AI-driven business environment, data readiness is instrumental in making informative decisions, managing risks effectively, and ensuring agility. Forbes Technology Council acknowledges data readiness as the key to unlocking the full potential of AI and driving sustainable growth.
- As more organizations integrate agents into their AI strategy and invest in scalable, flexible data strategies, data readiness transitions from a technical concern to a business imperative. This empowers businesses to harness the value of their data and stay competitive in the ever-evolving digital landscape.
