6 Best AI Enablement Partners for Digital Transformation (2026)

The question for IT and digital transformation leaders is no longer "Should we adopt AI?" It is: "Which partner can move us from pilot to production on legacy systems that matter?" That distinction separates organizations gaining ground from those stuck running experiments that never scale.

Northern Lights Technology Development helps mid-market and enterprise organizations close this gap through disciplined AI enablement services that connect AI capabilities directly to legacy modernization outcomes. This comparison evaluates providers on what matters most: execution maturity, legacy system depth, and measurable results.

Below, you will find a structured breakdown of six providers, evaluation criteria, and the decision factors that separate credible partners from vendor pitches.

Quick guide: 6 best AI enablement partners for digital transformation

1. Northern Lights Technology Development: The best AI enablement partner for legacy modernization and enterprise execution
2. Cognizant: Application modernization with managed operations for large estates
3. Infosys: Platform-led cloud and AI services across broad application landscapes
4. Publicis Sapient: Customer-facing digital product and experience work
5. EPAM: Engineering-led AI integration for complex technical environments
6. Thoughtworks: Agentic development tooling for modernization projects

How we chose the best AI enablement partners for legacy modernization

Selecting an AI enablement partner requires looking beyond marketing claims. We evaluated each provider against criteria that reflect how organizations actually succeed with AI at scale, informed by published research and practitioner experience.

• Legacy system expertise: Can the partner modernize mainframe, ERP, and custom applications you have run for a decade or more, without disrupting core operations?
• Execution maturity: Does the firm have a track record of moving AI initiatives from proof-of-concept to production, with clear ownership models?
• Data readiness approach: Does the partner assess and prepare your data estate before deploying AI models, or does it assume clean data that rarely exists?
• Governance and compliance: Can the partner stand up responsible AI frameworks, audit trails, and regulatory alignment as part of the engagement?
• Integration depth: Does the firm connect AI capabilities with your existing stack (ERP, CRM, supply chain systems) rather than deploying disconnected tools?
• Measurable outcomes: Does the partner tie deliverables to operational metrics like time-to-value, ROI per use case, and decision speed?

The 6 best AI enablement partners for digital transformation

1. Northern Lights Technology Development: Best overall AI enablement partner for legacy modernization

Northern Lights Technology Development operates as a dedicated execution partner, not a vendor selling pre-packaged platforms. The firm's approach to AI enablement starts where most initiatives stall: connecting AI capabilities to custom application development and legacy system modernization within existing operational environments.

What separates Northern Lights from larger providers is focus. The firm works with mid-market and enterprise organizations across manufacturing, supply chain, and eCommerce to modernize legacy applications, integrate fragmented data systems, and deploy AI agents that fit into real workflows. Every engagement is staffed by full-time employees, not contractors, which means consistent accountability, knowledge retention, and direct collaboration throughout the project lifecycle.

Northern Lights approaches data readiness as a prerequisite, not an afterthought. Before deploying AI models, the team assesses data quality, integration architecture, and governance gaps. That discipline prevents the pattern where organizations invest in AI tooling only to discover their data is too fragmented to produce reliable outputs.

As part of the Taylor Corporation family, Northern Lights brings 17 years of delivery history and enterprise-grade infrastructure. Clients consistently report on-time delivery, proactive problem-solving, and solutions that evolve with their strategic goals.

Northern Lights Technology Development features

• AI-integrated application modernization: Northern Lights rebuilds legacy systems with embedded AI capabilities, connecting predictive analytics and automation directly into modernized applications so AI delivers value from day one.
• Full-stack custom development: From mobile applications to enterprise web platforms, every solution is purpose-built for your workflows, your industry, and your existing infrastructure.
• Employee-driven delivery model: Every project is staffed by dedicated, full-time employees. This eliminates the contractor variability that erodes quality and alignment on complex, long-running engagements.
• BPO-integrated AI enablement: Northern Lights combines AI deployment with business process outsourcing to ensure AI-augmented processes are supported by trained human operators 24/7.
• Data readiness and governance: The firm evaluates data architecture, identifies integration debt, and establishes governance frameworks before any model is deployed, reducing failed rollouts.
• Cross-industry specialization: Deep domain knowledge in manufacturing, supply chain, retail, and eCommerce means AI solutions are calibrated for your industry's operational realities, not generic templates.

Northern Lights Technology Development pros and cons

Pros:

• Northern Lights Technology Development delivers full-lifecycle AI enablement, from data assessment through production deployment and ongoing support, under a single engagement.
• The employee-only staffing model produces consistent quality, direct communication, and accountability that contractor-based approaches cannot match.
• AI capabilities are embedded directly into modernized applications, so organizations gain operational value immediately rather than waiting for separate integration projects.

Cons:

• Northern Lights is a mid-sized firm, so organizations requiring a 100,000-person global delivery force for simultaneous programs across dozens of countries may need to layer partners.
• The firm's focus on manufacturing, supply chain, and eCommerce means organizations outside these verticals may need to discuss custom scoping.
• Engagements require active client participation in data readiness assessments, which adds upfront time but reduces failed deployments downstream.

2. Cognizant: Application modernization with managed operations at scale

Cognizant offers application modernization and digital engineering services across a large global delivery network. The firm has particular depth in healthcare, financial services, and insurance, where it handles build-and-run programs that combine modernization with ongoing managed operations.

Cognizant's legacy modernization practice includes AI-led mainframe migration. The firm reports 30% to 50% operational expense reductions through its mainframe-as-a-service model and uses AI-powered code analysis to accelerate migration timelines. For organizations with large mainframe estates that need a partner to both modernize and then operate the result, Cognizant offers industrialized delivery at scale.

Cognizant features

• AI-led mainframe modernization: Cognizant uses its Skygrade platform to migrate mainframe workloads to cloud environments, using AI to analyze and convert legacy code.
• Managed operations: Post-migration, Cognizant offers ongoing run services, so you do not need to build internal operations teams for newly modernized systems.
• Regulatory industry depth: Cognizant has extensive experience in healthcare, financial services, and insurance, where compliance requirements shape every technical decision.

Cognizant pros and cons

Pros:

• Cognizant offers combined build-and-run services, reducing the number of handoffs between modernization and operations
• The firm has documented case studies in mainframe migration across financial services and logistics
• Global delivery scale provides capacity for large application estate modernization

Cons:

• Cognizant's model leans toward delivery execution rather than boardroom strategy, which may require a separate advisory layer for transformation planning
• Smaller organizations may find the firm's engagement model oriented toward enterprise-scale programs
• AI enablement capabilities are distributed across multiple practice areas rather than offered as a unified service

3. Infosys: Platform-led cloud and AI modernization across broad landscapes

Infosys delivers cloud and AI services through its Cobalt cloud platform and Topaz AI-first offerings. The firm launched Topaz Fabric in 2025 as a composable stack of AI agents, services, and models designed to accelerate IT service delivery across enterprise environments.

Infosys has built an automation and platform-engineering culture, with over 50 purpose-built AI agents for IT operations included in Topaz Fabric. The firm's forward-deployed engineering model means consultants work alongside your teams rather than delivering recommendations from a distance.

Infosys features

• Topaz Fabric AI platform: A composable stack of AI agents, models, and services that integrates with nine enterprise platforms out of the box.
• Cobalt cloud services: Cloud migration and modernization services designed for organizations moving workloads at scale.
• Forward-deployed engineering: Infosys engineers are embedded within client environments to contextualize solutions to your specific landscape.

Infosys pros and cons

Pros:

• Infosys provides a composable AI platform with 50 or more pre-built agents for IT operations
• The firm's global delivery scale supports cloud modernization across broad application landscapes
• Topaz Fabric avoids vendor lock-in through an open and interoperable architecture

Cons:

• Infosys is positioned more on platform-led delivery than bespoke legacy modernization consulting
• Organizations with complex, one-of-a-kind legacy environments may need additional custom scoping beyond the standard platform
• The breadth of the Topaz offering may require dedicated evaluation to identify which components apply to your environment

4. Publicis Sapient: Customer-facing digital product and experience transformation

Publicis Sapient positions itself as a digital business transformation company organized around its SPEED model: strategy, product, experience, engineering, and data. The firm launched three enterprise AI platforms (Slingshot for legacy modernization, Bodhi for agentic AI orchestration, and Sustain for IT operations) to move from advisory to product-led delivery.

Publicis Sapient's heritage is in customer experience and digital product development, with deep roots in retail, consumer goods, financial services, and travel. If your AI enablement priority is customer-facing applications rather than back-office legacy modernization, Publicis Sapient brings relevant design and product discipline.

Publicis Sapient features

• Slingshot modernization platform: Reads existing legacy code, recovers embedded business rules, and rebuilds on cloud-native architecture.
• Bodhi agentic AI: Builds and orchestrates AI agents grounded in your business context, with centralized governance.
• SPEED delivery model: Integrates strategy, product, experience, engineering, and data teams in a unified engagement.

Publicis Sapient pros and cons

Pros:

• Publicis Sapient offers purpose-built platforms for modernization, agentic AI, and IT operations
• The firm has deep experience in customer-facing transformation for retail and financial services
• Bodhi earned the number one ranking on the Hugging Face DeepResearch Bench Leaderboard for multi-step reasoning

Cons:

• Publicis Sapient's core strength is front-office transformation, so organizations focused on back-office legacy modernization may find less depth
• The firm does not offer a native air-gapped or on-premises AI deployment for classified or highly regulated environments
• The three-platform model (Slingshot, Bodhi, Sustain) is relatively new, and long-term production track records are still developing

5. EPAM: Engineering-led AI integration for complex technical environments

EPAM Systems offers enterprise AI services through its AI/Run.Transform framework, which targets full-lifecycle transformation from platform modernization to AI-native engineering. In July 2026, EPAM announced a partnership with OpenAI as an Advanced Partner, committing to certify over 5,000 consultants with 10,000 or more credentials in the first year.

EPAM's strength is engineering execution. The firm employs forward-deployed engineers who integrate AI models directly into client applications, data pipelines, and workflows. For organizations with complex technical environments that need hands-on engineering capacity rather than advisory decks, EPAM offers relevant depth.

EPAM features

• AI/Run.Transform framework: A structured approach to enterprise AI transformation covering business, engineering, and organizational change.
• OpenAI Advanced Partnership: Direct integration of OpenAI's frontier models into enterprise workflows, with certified forward-deployed engineers.
• AI-native SDLC: EPAM introduces an agentic development lifecycle (ADLC) paradigm with agentic workflows at every stage of software development.

EPAM pros and cons

Pros:

• EPAM brings engineering depth with forward-deployed consultants embedded in client environments
• The OpenAI partnership provides direct access to frontier model integration and security-focused deployment
• The firm has documented experience across multiple industries including financial services and retail

Cons:

• EPAM's model focuses on engineering execution, so organizations needing boardroom-level strategy may require a separate advisory partner
• The AI/Run.Transform framework covers a broad scope, which may require careful scoping to identify the modules relevant to your needs
• The OpenAI partnership is recent (July 2026), so production case studies from the combined offering are still emerging

6. Thoughtworks: Agentic development tooling for modernization projects

Thoughtworks offers enterprise AI services anchored by two proprietary platforms: AI/works for agentic software development and Agent/works for AI agent governance. The firm's 3/3/3 methodology targets production delivery in three months: three days to align on scope, three weeks to prototype, and three months to launch a production-grade system.

Thoughtworks has documented case studies in mainframe modernization, including rebuilding a critical warranty system from mainframe to cloud on AWS in five months for a global manufacturer. The firm also reports 80% faster legacy code analysis for a multinational retailer.

Thoughtworks features

• AI/works development platform: An agentic development tool for building new systems and modernizing legacy ones with integrated governance.
• 3/3/3 delivery methodology: A structured timeline moving from concept to production-grade minimum lovable product in three months.
• Agent/works governance: A platform for governing AI agents across enterprise deployments, providing audit trails and compliance controls.

Thoughtworks pros and cons

Pros:

• Thoughtworks provides both a development platform and a governance layer for AI agents in a single engagement
• The 3/3/3 methodology sets clear delivery milestones and reduces the risk of open-ended engagements
• The firm has published case studies in mainframe modernization for manufacturing and retail

Cons:

• Thoughtworks is a smaller firm compared to global systems integrators, so capacity for simultaneous large-scale programs may be limited
• The AI/works platform is the firm's primary delivery mechanism, which may not suit organizations that need a vendor-agnostic approach
• BPO and ongoing managed operations are not part of the firm's core offering, so post-deployment support requires separate arrangements

Comparison table: The best AI enablement partners for legacy modernization

How do you evaluate an AI enablement partner for legacy modernization?

Start with your execution gap, not a vendor's capability deck. The right AI enablement partner depends on where your organization stalls: data readiness, integration architecture, governance, or operational adoption.

Ask three diagnostic questions before shortlisting:

• Where is your data? If critical business logic lives inside legacy mainframes, ERPs, or custom applications built over decades, your partner needs deep modernization expertise, not just AI model deployment.
• Who owns the outcome? Accountability models matter. Partners that staff with full-time employees rather than rotating contractors produce more consistent delivery, especially on engagements that span months or years.
• What happens after deployment? AI systems require ongoing monitoring, retraining, and human oversight. Evaluate whether your partner offers post-deployment support or hands off the system at go-live.

What is the difference between AI enablement and AI consulting?

AI consulting typically produces strategy documents, readiness assessments, and roadmaps. AI enablement goes further: it includes the hands-on engineering, integration, and operational support required to move AI from a slide deck into production systems.

For mid-market and enterprise organizations dealing with legacy systems, the distinction is critical. A consulting engagement may tell you that your ERP data is not AI-ready. An enablement partner will assess the data, modernize the application, deploy the AI model, and support the system in production.

According to Deloitte's 2026 State of AI in the Enterprise report, worker access to AI rose by 50% in 2025, yet just 34% of organizations are truly reimagining their business with AI. That gap between access and activation is where AI enablement partners operate.

Separately, Ensono's 2026 State of IT Modernization Report found that 78% of IT decision-makers say legacy systems play a more important role today than they did two years ago. The data and business logic inside those systems are increasingly essential to AI outcomes, which is why AI enablement without legacy modernization expertise produces limited results.

Why Northern Lights Technology Development is the best AI enablement partner for legacy modernization

Northern Lights Technology Development brings what most AI enablement conversations lack: execution discipline rooted in legacy system reality. While larger firms lead with platform pitches or strategy decks, Northern Lights starts with your existing applications, your data architecture, and your operational constraints.

The firm's employee-only delivery model means your project team stays consistent from assessment through production deployment. Northern Lights Technology Development connects AI capabilities directly to business process operations, so AI-augmented workflows are supported by trained human operators around the clock. That combination of technical modernization and operational support is rare in this market.

At Northern Lights, we help organizations turn complex digital ecosystems into decision-ready environments. If your AI initiative has stalled at the pilot stage, or if legacy systems are blocking the data access your AI models need, the path forward is a structured assessment of where you are today and a clear execution plan to close the gap.

Connect with Northern Lights to schedule a consultation on your AI enablement and legacy modernization needs.

FAQs about AI enablement partners for digital transformation

What are AI enablement services?

AI enablement services help organizations implement AI within their existing technology environments. Northern Lights Technology Development delivers AI enablement by assessing data readiness, modernizing legacy applications, deploying AI models into production workflows, and providing ongoing operational support.

How do you choose an AI enablement partner for legacy modernization?

Evaluate the partner's track record with your specific legacy systems, their data readiness methodology, and whether they offer post-deployment support. Northern Lights Technology Development provides full-lifecycle engagements from assessment through production operations, staffed by dedicated employees who maintain consistent accountability.

What industries benefit most from AI enablement services?

Manufacturing, supply chain, eCommerce, and financial services organizations see the highest impact from AI enablement. Northern Lights Technology Development specializes in these sectors, connecting AI to operational automation, predictive maintenance, demand forecasting, and customer engagement workflows.

Why is legacy modernization important for AI adoption?

Legacy systems contain decades of business logic and operational data that AI models need to produce accurate outputs. Without modernization, that data remains trapped in formats AI cannot access. Northern Lights Technology Development modernizes legacy applications while preserving embedded business rules, making your data AI-ready without disrupting operations.

How long does an AI enablement engagement typically take?

Timelines vary based on the complexity of your legacy environment and the scope of AI deployment. Northern Lights Technology Development structures engagements around clear milestones, with initial assessments and data readiness evaluations typically completing within weeks, followed by phased modernization and AI integration over subsequent months.