Business Challenges

Exception, an AI consultancy, partnered with a public sector client facing operational inefficiencies in departments such as legal document review, procurement, meeting productivity, and business analysis. These challenges resulted in excessive time spent on repetitive tasks, hindering overall efficiency and value delivery. AI was selected as the optimal solution due to its capacity to automate routine processes, minimize human error, and manage large data volumes swiftly, ultimately reducing costs and freeing resources for strategic work.

Solution Selection and Implementation

To identify the right AI technologies, Exception collaborated closely with the client, evaluating options like natural language processing (NLP) for document analysis, machine learning for data handling, and workflow automation tools. The chosen solutions were tailored for seamless integration into existing operations. Key challenges during implementation included workflow adaptation and ethical integration, which were overcome through direct team collaboration and establishing ethical principles from the project's outset. These principles were cascaded from C-suite to operational levels, addressing varying impacts by role and seniority.

Measurable Impact and Success Metrics

Success was gauged by time savings and operational expenditure (OPEX) reductions, achieving a potential 5% OPEX saving per adopting division. AI implementation yielded dramatic efficiency gains:

• Interview transcription: Reduced from 1.5 hours to 10 minutes (89% savings).

• Excel data analysis: Up to 75% time reduction.

• Legal/project document reviews: 50–75% savings.

• Presentation creation: From 4 hours to 1 hour (75% savings).

• Meeting minutes/actions: 62.5% savings.

• Procurement data extraction: From 2 hours to 30 minutes.

• IT business analysis: 75% savings.

• Legal insights: 50–75% savings.

These improvements enhanced the client's ability to manage public finances effectively without increasing overheads, positively affecting employees by shifting focus to high-value tasks, and benefiting stakeholders through better service delivery.

Adherence to Ethical Principles

Ethical challenges were proactively identified and addressed from the start, varying by organizational role. Exception followed core AI ethics principles of fairness, transparency, and accountability, embedding them across all project phases to ensure employee comprehension of AI functions and impacts. Data practices included rigorous validation protocols for accuracy, reliability, and security. Transparency was ensured through explainable AI models providing clear decision rationales, supported by cultural training on AI interaction and output usage. Bias mitigation involved dataset reviews for fairness, model adjustments, and emphasizing user-led decision-making, especially with industry-standard models, alongside robust change management.

Lessons Learned and Future Sharing

Key lessons for Scottish businesses: Align AI with business goals and workflows, integrate ethics early, invest in training, and choose scalable solutions. Exception is eager to present this case study at Scottish AI Alliance networking events to share insights and foster AI adoption.