Are you struggling to deliver enterprise-wide success from AI initiatives? You’re not alone. According to a 2024 Forrester global study commissioned by SoftServe, only 22% of organizations achieved the outcomes they expected with Generative AI (Gen AI).

What’s behind the big gap in expectations?

We know Gen AI is here, it’s happening, and it’s changing the game. There is potential for streamlining operations, cutting costs, finding new revenue streams, and driving innovation like never before.

But the last few years have taught us that AI applications, and particularly Gen AI applications, are only as good as the data they are built on. And that’s where things get messy. Siloed data, critical systems resistant to modernization, and poor-quality data often result in data chaos. But before you despair, know that you’re not alone: In a separate study, 77% of companies we surveyed reported that no one in their organization has a comprehensive understanding of the data collected or how to access it.

This is a solvable problem.

The C-level is central to the solution

Many of the technology and business decision-makers we surveyed believe that the lack of targeted investment in data projects is due to leadership’s unfamiliarity with data’s ROI. Our survey indicated that 78% of VPs and 61% of directors — but just 44% of those at the C-level — believe their organization’s investment priorities are negatively impacted by leaders not fully understanding how to generate value from data.

Without an understanding among C-level decision-makers of the value of data management, investments in important data projects were often diverted to Gen AI initiatives that ultimately relied on the execution of those same data projects to be successful. And 73% of business and tech leaders believe their company has allocated funds or talent to the latest Gen AI trends at the expense of more valuable data and analytics initiatives.

We’ve seen that a data-strategy update with buy-in from the top is needed to gain the full advantages of initiatives like AI, and nearly all (98%) of survey respondents agree.

Your data strategy update: Perfection is not the goal

Businesses that prioritize effective data practices are better positioned to build new revenue streams, enhance efficiency, and monetize their data assets. In our survey, 44% of organizations are already unlocking new revenue streams through mature data management practices.

Data maturity — the ability to effectively manage, utilize, and extract value from data assets — is the bedrock upon which successful AI initiatives are built. It encompasses data governance, data quality, data accessibility, and data literacy, all of which are essential for enabling AI to reach its full potential.

But it is not an all-or-nothing proposition. Building a better data foundation requires strategic clarity to determine what projects will deliver the biggest impact. Understand your business goals first, and then determine the available technology to help you bring data sources together. This will help you prioritize data and AI initiatives to extract value sooner.

A new data playbook: Time for a strategic shift

As leaders, we need to view data in a different way and implement a new playbook designed for the age of AI. This involves:

Finding the gaps. Start with a comprehensive understanding of your current data maturity level, identify challenges, and define a clear roadmap for improvement aligned with your business objectives.

Establish ground rules. Develop a feasible set of rules to ensure data is accurate, consistent, and compliant with regulations.

Data platform modernization: Modernize data platforms to cloud-based solutions, data lakes, and warehouses, and adopt modern data management tools. Done with the right goals in mind, it doesn’t have to result in higher risk or business disruption.

Unified data: Break down data silos and integrate data regardless of its source.

A robust data infrastructure specific to your business and your data is essential. Google Cloud capabilities supported by SoftServe digital consulting experts can speed development, lower total costs, and ensure your AI applications are enterprise-ready.

Google Cloud brings AI directly to your data with seamlessly integrated services like Gemini Enterprise, Vertex AI, and BigQuery. BigQuery’s embedded AI features make it possible to determine if the data you have is sufficient for AI actions and allow you to easily prepare data for model training in Vertex AI.

Get AI ROI by leading with data

Refocusing your efforts on a good foundation is the best way to deliver the full potential that AI can bring to your business. Let SoftServe and Google Cloud be your partners in this transformative journey.

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