Every time a forecast is made about the growth in demand and applications of AI, it seems as though the actual rate of innovation and adoption outpaces it. Currently, IDC forecasts GenAI spending will skyrocket to more than US$202 billion by 2028, driven by a belief that GenAI-infused products are key to future competitiveness. At that rate of growth, AI adoption will effectively become ubiquitous.
The challenge is the same bugbear that haunted digital transformation a decade or so ago: While budgets are ballooning, the journey from GenAI experimentation to production-level deployment has proven to be more complicated than expected. Consider how Gartner anticipates that 30% of generative AI projects will be abandoned after the proof of concept stage.
When you break this down, the underlying key challenge is easy to understand. It’s data.
The data dilemma
In running their AI trials, data leaders consistently cite issues like data reliability, privacy concerns, and the responsible use of AI as major roadblocks. This is particularly acute in data-sensitive sectors like banking, financial services, insurance (BFSI), and the public sector, where trust is paramount.
Informatica, a leader in AI-powered cloud data management, has doubled down on its partnership with Amazon Web Services (AWS) to find solutions to these data hurdles. The companies are now delivering integrated capabilities designed to fast-track enterprise-grade GenAI projects—securely, responsibly, and at scale.
“GenAI is only as good as the data that powers it,” said Rik Tamm-Daniels, Global Vice President for Ecosystems and Technology, Informatica. “Without trusted, secure, and high-quality data, even the most advanced AI models won’t yield the value enterprises are counting on. That’s where our expanded AWS collaboration comes in—making it easier for organisations to innovate with confidence.”
For GenAI to be able to produce quality text, images, code, and more, the data sitting behind it needs to be accurate, timely, and responsible. This is the source of the headaches for CIOs and data teams.
Disparate data sources, poor data quality, lack of security, and insufficient governance often undermine AI initiatives before they begin. Moreover, enterprises struggle with technical complexity, a lack of internal skills, and immature AI governance frameworks.
“We’ve heard repeatedly from leaders that they want to innovate, but they also want to do it right,” Rik Tamm-Daniels said. “That means ensuring data privacy, transparency, and compliance aren’t afterthoughts—they’re baked in from the start.”
Unifying data, governance, and privacy into a single platform
Informatica’s work with AWS creates an environment that allows enterprises to address all these foundational headaches.
Key innovations within this partnership include:
- Enterprise GenAI Blueprints and Automation Recipes on Amazon Bedrock: Pre-configured templates help businesses build and scale GenAI applications using best practices in data security, governance, and architecture
- Integration with Amazon SageMaker Lakehouse: This strategic partnership helps enterprises create next-generation data architectures, ensuring seamless access to data across warehouses, lakes, and analytics platforms—optimising for both AI and business intelligence
- Support for AWS PrivateLink Resource Endpoints: By leveraging PrivateLink, organisations can access Informatica’s advanced serverless data integration in a secure, isolated environment—ideal for highly regulated sectors that demand stringent controls
“We’re giving enterprises a fast track to GenAI maturity,” Alex Newman, Country Manager, Australia & New Zealand, Informatica. “With our platform, they can deploy GenAI solutions confidently — knowing their data is secure, their models are auditable, and their outcomes are reliable.”
By unifying data pipelines, governance, metadata, and privacy controls across hybrid and multi-cloud environments, Informatica empowers enterprises to build and deploy enterprise-ready GenAI applications at scale.
Having the foundations in place means democratized data access and use across the organisation without added risk. This encourages innovation and allows the organisation to adopt an agile approach to everything they do.
It also means that from the boardroom to the customer experience, there is an accelerated time-to-value. IT leaders can demonstrate the value of the AI investment more quickly, reducing the risk that the model will fall into the 30% that are discarded.
“The future belongs to companies who get their data right,” Alex Newman said. “Whether you’re building the next AI-powered app or reimagining customer experiences, data is your competitive advantage—and we’re here to help you unlock it.”
With a broad innovation agenda spanning GenAI, analytics, and open data platforms, Informatica is positioning itself as a cornerstone of enterprise AI transformation. This is not investment for the sake of it. It’s an effort to ensure that AI ambitions stick by being ethical, secure, and sustainable.
“We’re moving beyond the hype to deliver real-world results,” Rik Tamm-Daniels concluded. “With Informatica and AWS, enterprises finally have the tools they need to take GenAI out of the lab and into the heart of their business.”
