Scaling AI: Why BPM excellence is the missing link in AI transformation

As more and more businesses continue to integrate generative AI and machine learning into core business functions, enterprises face a sobering reality: the majority of AI projects fail. Industry analysts, including Gartner, consistently report that most AI initiatives struggle to deliver expected value, with failure rates often cited between 30% and 60%, due to issues such as poor data quality, compliance blind spots, and operational inefficiencies. Meanwhile, global compliance mandates like the EU AI Act are adding new layers of complexity, with recent estimates suggesting implementation costs for regulatory compliance can be substantial, sometimes reaching as high as $3.7 million per organisation depending on risk level and scope (Centre for Data Innovation, Gartner). 

So, what’s missing? 

When businesses invest resources into model development, they need to address the hidden costs in the manual, time-consuming processes that support AI at scale, such as, training, validation, compliance, and governance. That’s where business process management (BPM) emerges as a vital force for change. 

AI needs more than algorithms. It needs governance and scale 

The promise of AI lies in its potential to transform customer experiences, optimise decisions, and unlock new business models. But for AI to be enterprise-ready, it must be trained, tested, validated, and audited with the same rigour as any other critical business process. 

That’s not easy when: 

• Industry research indicates that 41% of internal team time is spent on data cleansing and model validation (Gartner, McKinsey, 2024) 

• 78% of suppliers lack AI governance capabilities (IDC, 2024) 

• Production models suffer a 42% drop in accuracy within six months (Gartner, 2025) 

Enter, BPM-powered AI enablement, where process excellence meets model performance. 

AI enablement through BPM 

AI thrives on patterns. BPM helps define, model, and standardise processes and patterns, making them understandable to both humans and machines. Without BPM, AI may be applied haphazardly, leading to fragmented automation, inconsistent results, and increased technical debt. 

AI enablement through BPM offers a structured, scalable path for organisations struggling to embed AI into their operations. Rather than relying solely on technical development, BPM integrates the people, processes, and governance needed to make AI work in the real world. This approach ensures that AI models are trained on high-quality, validated data, continuously audited for bias and accuracy, and deployed in compliance with evolving regulations like the EU AI Act. For organisations overwhelmed by operational bottlenecks, talent shortages, or compliance complexity, BPM-led AI enablement provides a way to accelerate adoption, reduce risk, and free up internal teams to focus on innovation and strategic growth. 

With BPM, processes are already mapped and monitored, giving AI access to high-quality, labelled data. This accelerates AI training, helps validate model predictions, and ensures relevance to real-world workflows. 

AI in practice: Driving accuracy, cost efficiency, and compliance 

BPM ensures that AI initiatives are driven by actual business needs, not just technical capability. It helps identify the right use cases for AI, such as optimising customer journeys, improving compliance, or streamlining operations. 

Many AI applications, like decision support or intelligent automation, require human-in-the-loop oversight. BPM orchestrates how and when humans should intervene, review, or override AI decisions, ensuring ethical, accurate and cost-effective outcomes. 

One of NashTech’s global technology clients—serving a multilingual customer base—faced a major challenge: how to validate and improve AI-generated outputs across 160 million data points in 28 languages. Our BPM solution deployed more than 650 human-in-the-loop auditors to conduct precise data checks, resulting in a 99% accuracy rate and vastly improved customer satisfaction. 

Outcomes we consistently deliver: 

• >98.5% data accuracy, significantly outperforming typical industry benchmarks  

• 50% cost savings by leveraging offshore teams 

• 15,000+ innovation hours redirected annually by freeing up internal talent 

• Complete risk transfer with SLA-backed auditing and governance frameworks 

BPM also includes performance measurement and feedback loops, allowing AI to learn from outcomes and adapt. It supports process mining and task mining, which uncover hidden inefficiencies and identify new opportunities for AI augmentation. 

Why enterprises need BPM to future-proof AI 

AI models, platforms, and regulatory landscapes will evolve. BPM provides the flexibility and documentation needed to update AI systems without rebuilding everything from scratch. It allows enterprises to swap or upgrade AI components while maintaining continuity in business operations. AI is a business capability that businesses must scale responsibly and ethically, and that requires more than data scientists and software; it demands disciplined, multilingual, scalable processes.  

NashTech can help  

NashTech’s BPM foundation brings 22 years of experience operationalising AI workflows, backed by ISO-certified audit teams and the financial stability of $55B private equity ownership. 

We partner with global enterprises to address the foundational bottlenecks holding AI back. Our BPM-led AI training and governance solutions help organisations scale ethical AI faster, with greater confidence, and at significantly lower cost. 

By auditing over 300 million data points annually and delivering a 98.5% accuracy rate (well above the industry average), we enable our clients to meet their AI objectives while freeing up internal teams to focus on innovation. 

Key BPM-AI support services include: 

• Human-in-the-loop validation in 28 languages for multilingual bias detection 

• AI auditing for regulatory compliance (GDPR, EU AI Act) and ethical AI certification 

• Data annotation, translation, and augmentation to power large language models (LLMs) 

• MLOps integration for smoother deployment and reduced model drift 
• Scalable support, with the ability to flex from 50 to 500 FTEs across 5 global hubs 

Interested in assessing your AI process maturity? 
Let’s talk. Visit https://www.nashtechglobal.com/contact-us/ to schedule a consultation.