Inside Ansira’s AI transformation journey

As AI adoption accelerated across the marketing technology landscape, Ansira recognized an opportunity to further unify its data, modernize workflows, and elevate AI literacy across the organization. Through a tailored transformation program, Ansira established an AI governance framework, introduced tiered training, and embedded AI capabilities across its platform and internal operations. As a result, AI adoption and literacy increased significantly, creating a secure, scalable foundation for continued innovation.

As an industry leader in marketing technology, Ansira was navigating the shift to AI-driven marketing alongside its clients. 

 By mid-2025, the rapid acceleration of AI presented a new opportunity: to further evolve internal operations, workforce enablement, and platform capabilities to meet emerging market expectations. 

With point solutions advancing quickly and client demand for AI capabilities increasing, Ansira recognized the need to move decisively. This moment of transformation highlighted several key areas for optimization across workflows and systems. 

Data fragmentation & quality  

With internal data spanning CRM, analytics platforms, content tools, and campaign infrastructures, Ansira identified an opportunity to create a more unified and connected data ecosystem. Strengthening data quality and connectivity became a critical step in ensuring AI-driven insights were reliable, consistent, and scalable across the organization. 

Technology integration complexity  

As demand for AI capabilities accelerated, Ansira recognized the immediate need to further evolve the AI features across its modules. Working against legacy integrations, inconsistent APIs between platform modules, and vendor overlap, each team found their own workaround to build, test, and ship AI capabilities. Yet, this fragmented approach highlighted the need for greater consistency and alignment across teams. 

Unclear use cases & ROI  

Early AI experiments produced promising pilots across content, reporting, and optimization. However, to fully realize this value at scale, Ansira identified the need for a more structured prioritization framework — one that aligned use cases to measurable business outcomes and focused investment on the highest-impact opportunities. 

Content supply chain bottlenecks  

Across managed services, many critical workflows — such as campaign setup, co-op claims auditing, performance reporting, and content production — remained highly coordinated and people-driven. Growing client demand created an opportunity to streamline processes and better leverage AI to improve efficiency and consistency across delivery. 

Organizational resistance & skill gaps  

AI literacy across the workforce was uneven. A small number of technically engaged employees were actively using AI tools, but the broader organization — client partnership, content strategists, account teams — had limited exposure and mixed feelings about what AI meant for their roles. This highlighted an opportunity to expand AI literacy and equip employees with the skills and confidence to integrate AI into their day-to-day work. 

Operating model misalignment  

Ansira’s structure was built for campaign-based, channel-centric, human-driven delivery. AI-first operations require the opposite: always-on decisioning, continuous optimization loops, and cross-functional collaboration between marketing, data, and engineering. The gap between those two models could not be closed by tools alone, and the need to evolve toward a more integrated, cross-functional model was revealed. 

Governance, compliance & brand risk  

As AI adoption expanded, Ansira identified an opportunity to bring greater consistency and visibility to how tools were used across the organization. Multiple versions and legacy instances of AI tools existed across teams, making it difficult to capture shared learnings, measure usage, and scale best practices. Establishing a more unified governance approach and clear standards became a priority, to ensure more consistent adoption, improved transparency, and the ability to scale AI responsibly across the business. 

Scaling from pilot to production  

Ansira successfully demonstrated the value of AI through targeted pilots. The next phase focused on operationalizing these successes — standardizing workflows, enabling teams at scale, and embedding AI into repeatable processes to support long-term, sustainable impact. 

Ansira began with a structured discovery engagement, working across their own organization — from C-suite leadership and functional executives to team leads in marketing, engineering, product, and operations. The goal was not just to determine which AI tools to deploy, but to better understand the underlying factors influencing adoption and the structural changes needed to support scalable, lasting impact. 

The assessment covered five dimensions: 

• Market context 

• Technology & data infrastructure 

• Workforce readiness 

• Use case landscape 

• Governance & compliance posture 

Ansira found that technology was not the main obstacle. They had access to capable AI platforms. Instead, the opportunity was to strengthen the structures needed to support it: governance, workforce readiness, and operating model alignment. 

Based on the full-spectrum assessment, Ansira deployed a dedicated transformation team and designed an AI transformation program from scratch. Every workstream, training module, governance document, and product integration was purpose-built for their own operating context. 

The transformation included a parallel-track program to improve all three problem areas at once: governance, workforce readiness, and operating model alignment. Three coordinated workstreams ran simultaneously, each reinforcing the others and managed as a single, integrated transformation with shared milestones and executive accountability. 

Governance foundation  

Ansira built the policy and compliance infrastructure needed to make AI safe to scale. This included authoring a comprehensive AI Governance Policy covering acceptable use, data handling, risk classification, and vendor accountability. Ansira designed and operationalized a structured AI use case intake process — requiring every new AI initiative to pass evaluation for business value, data sensitivity, and client impact before deployment.  

Simultaneously, Ansira implemented ISO/IEC 42001, the international standard for AI management systems, including audit preparation and gap remediation. The Phase 1 audit was completed in Q1 2026 with only minor findings. 

Workforce enablement  

Ansira designed and delivered a tiered AI training curriculum, tailored by role, function, and level of technical depth. The program ran three levels: 

• Essentials (foundational literacy for all employees) 

• In Practice (applied AI skills for active practitioners) 

• Champions (advanced users trained to lead adoption within their departments) 

A separate leadership track equipped executives and team leads with the strategic understanding and governance accountability needed to sponsor transformation from the top. Across the organization, Ansira trained and activated a network of AI Champions embedded in every client-serving department — creating internal capability that would outlast the engagement. 

Product AI integration  

Ansira’s engineering and product teams embedded AI capabilities across the company’s SaaS platform. New AI features were delivered across four core modules: 

• Automated compliance review 

• AI-assisted claims auditing 

• Intelligent social activation 

• Natural-language analytics querying 

To accelerate delivery, Ansira provisioned and rolled out AI coding tools — including Claude Code — across 230 developers, with structured onboarding to drive active adoption. 

As a result of the transformation plan, two results stand out: the enterprise enablement platform generated 10,564 hours of productivity gains (equivalent to ~20 FTEs worth of working time, at 520 hours/FTE/quarter) in a single quarter, and enterprise recurrent usage reached 87%, surpassing the original full-year target of 85% nine months ahead of schedule.

Lastly, 73% of the workforce completed mandatory AI governance training, establishing a compliance-ready foundation for scaled AI adoption. 

Paul Tibbitt, Chief Executive Officer at Ansira, said it best: “The combination of enterprise AI tools and the governance framework we have built gives our clients something rare: AI that is both powerful and safe. That is the foundation everything else is built on.”