AI compliance begins with realism
AI regulation is now a defining issue for the UK economy. The Governor of the Bank of England, Andrew Bailey, recently urged regulators and industry to take a pragmatic and open-minded approach to Artificial Intelligence.
He warned that while AI presents opportunities for productivity and innovation, it also carries risks that must be managed rather than feared. His comments, reported by Reuters, reflect a broader shift in tone across the United Kingdom: moving away from over-cautious hesitation and towards practical, evidence-based governance.
This reflects how AI regulation must evolve alongside innovation. At askelie we see this as an important step forward. True progress in AI requires both innovation and compliance. Pragmatism should never mean loosening standards. It means designing systems that meet the highest levels of security, transparency and accountability without stifling creativity.
The meaning of pragmatic AI regulation
True AI regulation should be adaptive, not restrictive. Pragmatic regulation is not about letting technology run unchecked. It is about shaping rules that keep pace with innovation. Regulators are acknowledging that the old model of reactive oversight no longer works.
The Bank of England’s position echoes what many leaders in government and academia have been saying for months: that the UK’s future competitiveness depends on its ability to balance growth with responsible governance. This shift also connects to the proposed Artificial Intelligence Regulation Bill, which aims to fill the gap between ethical guidance and enforceable law. It underlines the growing expectation that all organisations using AI will need clear audit trails, explainable outcomes and mechanisms for accountability.
A shared responsibility between regulators and innovators
AskELIE was built to help organisations comply with modern AI regulation standards automatically. Andrew Bailey’s message was clear: AI risk cannot be managed by regulators alone. It requires shared responsibility across financial institutions, developers, and policymakers. That principle aligns directly with AskELIE’s mission.
Our Ever Learning Intelligent Engine (ELIE) provides the structure for responsible automation. It allows organisations to deploy AI that is transparent, traceable and secure. By integrating evidence tracking, version control and audit logging into every workflow, AskELIE ensures compliance is part of the process, not an afterthought.
Lessons from the financial sector
The FCA’s sandbox is a model of proactive AI regulation done right. The financial sector often acts as a testing ground for governance. Earlier this year, the Financial Conduct Authority launched an AI sandbox in partnership with Nvidia to test machine-learning models safely before market deployment.
It shows how regulators are starting to enable responsible experimentation. Rather than banning new technology, they are creating environments where innovation and oversight can coexist. AskELIE supports this approach. We believe that if AI models are tested, monitored and validated in controlled environments before going live, risk can be minimised while maintaining agility.
Our ELIE Capture and ELIE Composer tools already make this possible for enterprises developing and deploying AI internally.
Why pragmatic regulation matters for business
Every enterprise that uses data-driven systems must prove its adherence to AI regulation principles. For businesses across the UK, the call for pragmatic AI oversight is good news. It encourages innovation without increasing uncertainty. However, it also raises the bar.
Companies must now prove that their AI systems are reliable, fair and compliant. That means building infrastructure for explainability, bias monitoring and data lineage. At askelie we often see organisations treat AI compliance as a bolt-on project, handled by legal teams long after systems have been built. That approach is expensive and unsustainable.
Pragmatism requires foresight. The time to embed compliance is during design, not at the end.
Practical steps towards AI governance
AskELIE’s architecture enables proof of compliance under emerging AI regulation frameworks. Every organisation can take three immediate actions to align with this new regulatory direction.
1. Build transparency into the design
Ensure every AI decision can be traced back to its data source, model version and human reviewer. This provides the audit trail regulators expect. AskELIE’s platform automates this documentation to make compliance effortless.
2. Treat AI compliance as continuous
AI models change over time. Drift, data bias and shifting context can introduce risk. Ongoing monitoring, alerts and retraining must be part of governance.
Tools such as ELIE for Contracts help organisations maintain up-to-date oversight across connected systems.
3. Prioritise ethical outcomes
Compliance alone is not enough. Ethical design should be a business advantage. Accessible, explainable and fair AI systems are not only safer but also more trusted by customers.
Our accessibility module, AskVERA, applies these same principles to content design, proving that inclusion and compliance strengthen one another.
Pragmatic regulation still demands evidence
While the Bank of England calls for flexibility, it also expects proof. Evidence of responsible practice will determine who gains regulatory trust.
AskELIE’s architecture enables organisations to capture this proof automatically through metadata, audit logs and permission-based validation. This creates what we call a “living compliance record”, always current, always verifiable.
For example, if a bank uses AI for credit scoring, regulators can see exactly which data fields influenced a decision and who approved the model’s use. That is not theoretical. It is built into the AskELIE platform today.
Challenges that remain
Consistency between UK and EU AI regulation will be vital for trade and innovation. Pragmatic regulation will not solve everything overnight. Smaller organisations may still struggle with compliance costs. International alignment will take time.
Definitions of “fairness” and “transparency” will continue to evolve. However, the direction is clear. The United Kingdom intends to become a leader in safe, explainable and trustworthy AI. That means compliance will soon be non-negotiable.
The organisations that prepare now will gain a long-term advantage.
The importance of trust in the age of automation
Trust is the foundation of any digital economy. In the same week as the Bank of England’s remarks, the Financial Times reported concerns about HMRC using AI to assess R&D tax claims without transparency (FT report).
The reaction was swift: businesses called for clearer explanations of how AI decisions are made. This reinforces the message that AI systems must remain accountable.
When organisations explain their logic and show evidence, they build confidence. When they do not, they lose it. AskELIE helps avoid that by providing explainability and validation tools that make every AI output auditable and understandable.
Looking forward
The Bank of England’s intervention is a reminder that regulation and innovation are not enemies. They are partners in progress.
Pragmatic regulation gives responsible companies the confidence to innovate while keeping society safe. AskELIE was created for this environment.
Our platform helps organisations move faster, comply with evolving standards and document every action with precision. As UK regulators define the next phase of AI oversight, AskELIE stands ready to help enterprises, councils and institutions build AI they can defend and trust.
Final thought
As AI regulation continues to mature, the organisations that build responsibly will lead the way.
The future of AI in the UK will be defined by how well we combine innovation with accountability. Pragmatism must never mean compromise.
It means building intelligent systems that work safely, explainably and fairly from day one. At askelie we call that progress with purpose.
AI compliance is not bureaucracy. It is the foundation for trust, growth and competitive advantage.