6Cs Trend 5: Customisation of AI and AI Agents to Workplace Needs

By Kevin Shepherdson, CEO & Founder, Straits Interactive

In 2025, Generative AI and autonomous AI agents are transforming workplaces across industries. "Customisation," the fifth trend in the "6Cs" framework, highlights how businesses can tailor AI systems and agents to specific tasks and workflows to unlock unparalleled efficiency, innovation, and productivity. For small and medium-sized enterprises (SMEs), this presents unique opportunities and challenges as they navigate the integration of tailored AI solutions.

This article explores key trends, real-world examples, challenges, actionable recommendations for SMEs, and the role of AI agents in workplace transformation.

What are AI Agents?

AI agents are autonomous systems that interact with their environment to perform specific tasks without constant human intervention. Equipped with generative AI, natural language processing, and predictive analytics, these agents can:

1. Automate repetitive tasks.

2. Provide real-time insights and recommendations.

3. Collaborate with employees on complex workflows.

4. Continuously learn and adapt based on new data.

Relevance to SMEs

For SMEs, AI agents offer cost-effective solutions to scale operations and enhance productivity. For instance, an AI agent can automate the creation of business proposals by conducting web searches for relevant information and scheduling client meetings by sending calendar invites automatically. Additionally, upcoming features and functionalities in Microsoft’s Co-Pilot offerings and Co-Pilot Studio are incorporating AI agents, further streamlining business processes.

Key Trends in AI Customisation for 2025

1. Industry-Specific AI Solutions

AI systems are increasingly fine-tuned for unique workflows in various industries.

1. Education/Training: AI agents automate tasks like attendance tracking, personalised lesson planning, and student performance monitoring.

2. Retail: Inventory management tools predict demand and optimise supply chains.

3. Manufacturing: Custom AI monitors equipment performance and predicts maintenance needs.

Example: A professional training institute deployed an AI-powered agent to create individualised training modules for employees based on their performance data. This led to a 30% improvement in training outcomes and reduced trainer workload.

2. Departmental Customisation

Custom AI tools are now addressing specific departmental needs.

1. HR: Automated candidate screening, onboarding processes, and training programmes.

2. Customer Service: AI agents handle routine queries, escalate complex cases to human agents, and provide real-time support.

3. Marketing: Tools analyse customer sentiment and optimise campaign strategies.

Example: A small e-commerce company integrated an AI-powered customer service chatbot to handle common inquiries. This reduced response times by 40% and allowed human agents to focus on higher-value interactions.

3. Employee-Driven AI

No-code and low-code platforms empower employees to create and adapt AI tools.

1. Teams design AI agents tailored to their day-to-day needs without relying on IT departments.

2. Personalised AI assistants help employees automate repetitive tasks, like scheduling or data entry.

Example: A customer service team at an SME used a no-code platform to build an AI agent for categorising and prioritising customer inquiries. The agent automatically sorted tickets based on urgency and forwarded them to the appropriate departments, improving resolution times and team efficiency.

4. Proactive and Predictive AI Agents

AI agents are evolving to anticipate needs and offer recommendations.

1. Suggest workflow optimisations.

2. Predict potential issues in supply chains or customer behavior.

3. Support strategic decision-making in sales and marketing.

Example: A small retail company used a predictive AI agent to analyse customer purchase data and suggest personalised sales campaigns. The system identified trends and recommended targeted offers, resulting in a 25% increase in campaign conversion rates.

Challenges SMEs Face in Customising AI Solutions

1. Limited Resources

SMEs often lack the budget and technical expertise to adopt and customise advanced AI solutions.

2. Data Availability and Quality

Many SMEs struggle to collect, clean, and structure the data needed for effective AI customisation.

3. Integration with Existing Systems

Legacy systems in SMEs may not be compatible with modern AI tools, creating technical barriers.

4. Ethical and Regulatory Concerns

SMEs must navigate data privacy regulations and ensure ethical AI deployment to avoid reputational risks.

Actionable Recommendations for SMEs

1. Start Small with No-Code Platforms

1. Leverage platforms like Capabara or Microsoft Co-Pilot to design simple AI tools tailored to immediate needs.

2. Empower employees with basic training to develop and manage these tools.

Tip: Begin with a pilot project in a single department (e.g., customer service) to test the impact and scalability of customised AI.

2. Partner with Technology Providers

1. Collaborate with AI vendors who offer pre-trained models tailored to specific industries.

2. Opt for cloud-based solutions to minimise upfront infrastructure costs.

Tip: Seek providers that offer subscription-based pricing to manage cash flow effectively.

3. Focus on Data Readiness

1. Invest in cleaning and organising existing data to ensure it is AI-ready.

2. Use third-party services for data annotation if internal resources are limited.

Tip: Start by integrating publicly available datasets to enhance your proprietary data for training AI models.

4. Prioritise Ethics and Governance

1. Implement clear guidelines for data privacy and security to align with regulations like GDPR or PDPA.

2. Regularly audit AI tools for biases and inaccuracies.

Tip: Use explainable AI (XAI) systems to enhance transparency and trust with stakeholders.

5. Measure ROI and Iterate

1. Set clear metrics to measure the return on investment (ROI) for AI deployments, such as time saved, cost reductions, or increased revenue.

2. Use feedback loops to improve AI tools based on real-world usage.

Tip: Schedule quarterly reviews to assess AI performance and adapt tools to changing business needs.

The Future of AI Customisation for SMEs

As Generative AI and AI agents become more accessible, SMEs have unprecedented opportunities to streamline operations and drive innovation. By focusing on tailored solutions, empowering employees, and addressing key challenges, businesses can unlock the full potential of these transformative technologies.

In 2025, AI customisation will not only level the playing field for SMEs but also allow them to thrive in a competitive landscape. With a clear strategy and thoughtful implementation, even small businesses can harness the power of AI to achieve big results.

This article is part 5 of a 6-part series Generative AI in the Workplace: 6 Trends Every Organisation Should Take Note of in 2025.