A guide to including AI in your digital transformation strategy

07 Mar, 2024

Artificial intelligence, or AI, has become synonymous with innovation, efficiency, and transformative potential. As your organisation embarks on the journey of digital transformation, understanding AI is essential to effectively harness its capabilities.

What is AI?

AI refers to the simulation of human intelligence in computer systems programmed to problem-solve and learn. AI is capable of performing tasks that historically required human intelligence; tasks such as recognising speech, making decisions, and identifying patterns.

At its core, AI involves the development of algorithms that enable machines to analyse data, recognise patterns, and make decisions with minimal human intervention. This technological leap has profound implications for the financial services, banking, superannuation and insurance sectors. AI offers opportunities for enhanced CX (customer experience), improved operational efficiency, and strategic decision-making.

This guide provides some key considerations for successful AI adoption into a digital transformation strategy.

1. Start with your business goals

As with any systems, operational or process change you plan to introduce during digital transformation, it is important to align AI adoption with your organisation’s strategic goals and business objectives. Identify areas where AI can drive value, whether it’s streamlining processes, improving customer engagement, or optimising risk management. A targeted, business-centric approach ensures that AI investments directly contribute to overall success.

2. Get you data in order

Effective AI relies on quality data. Evaluate your data infrastructure, ensuring it is robust, accessible, and compliant with regulatory requirements for your sector, including data privacy principles and legislation. Implement data governance practices that prioritise security and privacy. Develop a data strategy that facilitates the seamless integration of AI applications, leveraging both structured and unstructured data.

3. Select the right technology stack

Assess your existing technology infrastructure to determine its readiness for AI integration. Consider the scalability, flexibility, and compatibility of your systems. Choose a technology stack that supports the deployment and management of AI solutions. Cloud readiness and integration capabilities are crucial aspects to evaluate in this process.

4. Build a skilled team

Invest in developing or augmenting a skilled workforce equipped with the knowledge required for AI implementation. Assess existing talent, identify gaps, and provide training programs to upskill your team. Hiring professionals with expertise in AI, machine learning, and data science ensures a solid foundation for successful AI adoption.

5. Consider regulatory compliance

Know your sector and make sure your innovations don’t introduce regulatory risk. The regulatory environment is stringent in many sectors, including financial services, banking, insurance and health so ensure that your AI initiatives align with industry standards and legal requirements. Develop a comprehensive understanding of data privacy, transparency, and ethical considerations. This approach safeguards your organisation against compliance risks associated with AI applications.

6. Implement with CX in mind

Prioritise AI applications that enhance the customer experience. Whether it’s personalised services, improved security features, or efficient communication channels, adopting AI should positively impact your customers. If you can tailor AI solutions to meet customer expectations, for example with transparent and user-friendly interfaces, you’ll build trust.

7. Strengthen cyber security measures

The integration of AI introduces new dimensions of cyber security challenges. Evaluate and enhance your cyber security infrastructure to address potential threats and vulnerabilities associated with AI applications. Establish robust protocols for continuous monitoring, threat detection, and incident response to safeguard against evolving cyber security risks.

8. Test and validate with pilot projects

Before full-scale implementation, run pilot projects and proof-of-concept studies. This allows you to validate the feasibility, performance, and real-world impact of AI applications in controlled environments. Use the insights gained from these initiatives to refine and optimise your AI solutions for broader deployment.

9. Check scalability and future proof

Ensure that your AI infrastructure and solutions are scalable to accommodate future growth. Stay informed about emerging technologies and industry trends to future-proof your AI investments. A forward-thinking approach allows your organisation to adapt to evolving market dynamics and maintain a competitive edge.

10. Foster a culture of adaptation

AI adoption is an ongoing journey of learning and adaptation. Cultivate a workplace culture that encourages continuous improvement, collaboration, and innovation. Facilitate knowledge sharing, cross-departmental collaboration, and stay connected with the broader industry to stay informed about AI advancements.

If you’re excited about incorporating AI into your digital transformation strategy, we’d love to hear from you. Start the conversation with 9yards digital transformation consultants today.

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