Evolving AI architecture to meet rising AI demands
Shawn Rogers2025-03-18 | 5 min read

Keeping pace with AI innovation is a daunting task. AI projects are impacted by executive and board level mandates, competitive pressures, new technology challenges and reliance on traditional processes and often legacy technology infrastructures. Only 39% of global respondents to BARC AI research indicate their organization is meeting their AI business objectives.*
In the same research report 331 practitioners listed security standards and compliance along with data access and use polices as the top priorities for a mature AI strategy, yet only 21% of the respondents can claim they have formalized their work on these important strategic initiatives.*
Future-proofing your AI strategy
So, why do AI projects struggle? It often boils down to foundational data challenges. Access, quality, compliance and regulatory issues can expose tedious and slow processes for enterprise professionals. Data scientists are forced to wait on their IT counterparts to approve access to and deploy the necessary data for AI projects. And IT workloads are only growing adding to delays that can be a choke point for project momentum.
These challenges become more impactful for companies that have complex, disparate data deployed in multicloud environments across multiple regions and countries. The challenge is even more complex for companies leveraging data from highly regulated industries like financial services, life sciences, and public sector; this data is often deployed on-premises creating a hybrid work environment that can be difficult and slow to navigate.

The tension that exists between access to data, AI and data governance and speed to insights needs to be addressed for companies to future proof their approach to AI. AI leaders are finding they require a smart, single control plane for data management that span cloud and on-premises systems to create a system of record while governing AI workflows, data use and access plus delivering the capability to manage compute assets to match workloads and to save money.
This combination creates the trust that powers AI to move at the speed of business and empower stakeholders (data scientists, IT, data engineers and line of business) to execute independently in a self-serve manner while staying compliant, auditable and within regulatory guidelines.
Coupling secure data management with compliance and auditability is a direct path to AI innovation. Eliminating the single point of control and access without loss of oversight and governance, is no longer optional for companies that want to thrive in this new AI era of innovation.
An often-overlooked challenge of AI projects is cost (data replication, orchestration and compute, GPU’s) play critical roles in cost overruns for AI budgets. The 21% of research respondents referenced above from BARC’s AI research list cost as their top challenge when executing on AI projects. The comprehensive architecture explained above will bring cost control into focus providing tools that eliminate data replications, granular controls to apply the correct compute to workloads and rich metadata and caching functionality that will enable users to monitor the impacts of cost and customize it to gain the highest level of ROI.
Next-level AI
As a company’s AI practice grows and becomes more complex it will need to expand its capabilities to achieve the speed necessary for AI success. The combination of secure data management, coupled with simplifying hybrid operations while maintaining trust and empowering users to self-serve in a governed environment is the path to next-level AI.
Domino Data Lab and NetApp are partnering to address these challenges. Follow these resources for more details:
- NetApp and Domino: AI anywhere - Unified enterprise AI platform
- Blog: Maximize AI Efficiency with Domino Volumes for NetApp ONTAP
- Demo video: Domino and NetApp - Domino Volumes for NetApp ONTAP
About BARC
BARC is a leading analyst firm for data & analytics and enterprise software with a reputation for unbiased and trusted advice. Our expert analysts deliver a wide range of research, events and advisory services for the data & analytics community. Our innovative research evaluates software and vendors rigorously and highlights market trends, delivering insights that enable our customers to innovate with data, analytics and AI. BARC’s 25 years of experience with data strategy & culture, data architecture, organization and software selection help clients transform into truly data-driven organizations.
*Source: Preparing and Delivering Data for AI, Adoption Trends, Requirements and Best Practices March 2025 370n
Shawn Rogers is the CEO of BARC US and lead AI analyst bringing over 28 years’ experience to the role. He is an internationally respected industry analyst, speaker, author and instructor on data, business intelligence, analytics, AI/ML and cloud technologies. His former executive strategy roles with Dell, Statistica, Quest software and TIBCO give him a unique perspective on the software industry.