Organizations are producing and capturing more data than ever before in history, but many are still fighting the decades-old battle to turn that data into value. Aging systems, siloed records, slow pipelines, and unclear ownership make data messy, inaccessible, and sometimes even risky to use.
Organizational leaders, meanwhile, are reading the writing on the wall that tells them they will need to get ahead of the AI adoption curve if they want to remain relevant in their industries in the next five years. But they know the path to AI success must make a pit stop at AI readiness, and they know their data simply isn’t ready.
To address this widening gap between where their data sits and where they want it to be, more and more leaders in this situation are wading into the world of data modernization services. These services transform fragmented, outdated data environments into governed, scalable, cloud-aligned foundations ready to support analytics, automation, and — you guessed it — those big AI use cases.
You may also have guessed that modernization means more than trading out old technology for a modern stack. It’s about establishing a usable data platform connective enough to fuel intelligence, innovation, and competitive advantage.
Why Modernization Matters More Than Ever
Modern enterprises face familiar challenges:
- Sprawling legacy estates slow down decision-making
- Data quality and usage varies wildly between teams
- Multiple versions of the truth erode trust in core systems
- Governance requirements are ramping up fast
- Talent shortages stall transformation in its infancy
Modernization addresses these faults holistically to ensure organizations don’t just store all those petabytes of data, because they need to be able to trust, share, and act on it.
That shift is critical for AI. Models reliant on bad inputs, inconsistent schemas, or poor governance become unreliable, unscalable, and potentially dangerous to train on. Put even more simply, modernization ensures the wiring works before the enterprise plugs in AI.
Data Modernization Services: The Foundation for AI Readiness
Think of AI like autonomous vehicles: possible only when roads, signals, and infrastructure are modernized enough to support them.
Without modernization, AI becomes a patchwork — exciting in pilot form but brittle or even unusable in production.
Production-ready AI depends on:
- Clean, governed data pipelines
- Flexible cloud infrastructure
- Accessible data catalogs and lineage
- Automated quality checks
- Responsible governance and compliance
- Operational MLOps and monitoring
With that solid foundation in place, AI scales safely and predictably, expanding business value rather than introducing risk.
Why External Data Modernization Partners Accelerate Progress
Many enterprises assume they can modernize internally — but without the rare team with all the right, hard-to-find skillsets, modernization hits a wall when tackled as a purely inside job.
There are several reasons leaders increasingly turn to specialist data modernization services providers:
- Speed and proven methodology: External partners have implementations, frameworks, and patterns already built — accelerating transformation beyond internal trial-and-error.
- Access to scarce skills: Data engineers, cloud architects, and MLOps talent remain hard to hire and retain. Services partners bring that capacity on demand.
- Cross-industry best practices: Partners see what works (and what fails) across many organizations, giving clients tried-and-tested modernization playbooks.
- Value-driven execution: Strong partners don’t modernize for technology’s sake, instead tying modernization milestones to business outcomes and, down the line, game-changing AI use cases.
- Accountability and lifecycle support: Modernization is ongoing; partners can operate and optimize platforms long after launch.
Industry research, including Hakkoda’s own State of Data report, reinforces that many enterprises now acknowledge they must modernize and also must seek outside expertise to do it effectively.
What Effective Data Modernization Services Include
A robust modernization program is phased, measurable, and designed for continuous value extraction.
Best-in-class data modernization services typically include:
- Assessment & Strategy: Mapping data maturity, identifying capability gaps, and aligning stakeholders.
- Architecture & Platform Build: Cloud-first storage, compute, identity, governance, and cost controls.
- Pipeline Engineering and Integration: Modular, observable, high-quality data movement and modeling.
- Governance and Compliance: Policies, definitions, lineage, access controls, classification, and automation.
- AI Enablement: Feature stores, experimentation frameworks, CI/CD pipelines for models, and monitoring.
- Managed Services & Optimization: Ongoing enhancements, reliability engineering, and usage enablement.
Critically, modernization shouldn’t take years before value is realized. The best programs tie foundational upgrades to targeted AI or analytics pilots from day one — showing quick wins while building scalable capabilities.
Getting Modernization to Stick Organically
Successful modernization demands organizational alignment, not just engineering excellence. Enterprise leaders should:
- Establish product-oriented data ownership
- Roll out literacy and adoption programs
- Track quality, performance, cost, and business outcomes
- Scale patterns rather than reinventing them team-by-team
This is where partnering with experienced modernization service providers helps — they bring both delivery discipline and enterprise change enablement.
Where & Why Hakkoda Fits the Bill
Data modernization services are no longer optional — they’re the prerequisite for AI maturity, operational efficiency, regulatory compliance, and innovation at scale. Leaders increasingly recognize that while modernization can’t be avoided, it also shouldn’t be attempted alone. Hakkoda’s State of Data research reflects this trend, revealing broad agreement among enterprises that modernization requires external expertise and specialized support.
Hakkoda positions itself as that partner: an industry-sensitive approach that meets clients wherever they are on their modernization journey. Unlike firms that focus only on technology uplift or only on AI, Hakkoda works to build foundational modernization capabilities at the same time it deploys targeted AI use cases, ensuring organizations realize value fast while constructing durable, scalable platforms for the future.
Ready to get started? Talk to one of our enterprise data modernization experts today.
