Artificial Intelligence (AI) has the potential to revolutionise business operations by automating routine tasks and providing deep insights through data analysis. However, implementing AI into an organisation’s workplace does not occur overnight — it requires careful planning for businesses to experience real, tangible benefits.

To maximise AI’s transformative potential, companies must take a strategic approach to implementation. This includes establishing initiatives with business objectives and goals and setting clear metrics for success. This approach is crucial for harnessing AI’s power in complex, dynamic fields.

Strategic Implementation Over Speed

While companies may be in a rush to reap AI’s rewards, the key to successful AI adoption is in strategic implementation rather than rapid deployment.

While this is especially important in highly specialised industries like healthcare, where AI offers groundbreaking opportunities across diagnostics, treatments and operational efficiencies, a thoughtful approach will help organisations avoid wasted time and resources across sectors.  Hastiness only increases the possibility of AI failures during implementation, eroding trust with employees and customers. A more strategic, albeit slower, approach yields long-term benefits of enhanced accuracy, alignment with goals and sustainable integration.

According to recent Unisys research, 93% of executives believe AI will be a permanent part of their organisation’s strategies. While the technology holds great potential to enhance business outcomes, it is not a magical solution with instant results. For long-term, meaningful results, organisations should treat AI as a sophisticated tool that requires an equally advanced rollout.

Implementing AI into your Organisation

When implementing AI in a workplace, it is crucial to establish a clear ROI framework that aligns with business objectives. Justifying AI investments requires a thorough analysis that considers upfront costs, potential client benefits, and internal efficiencies. Even the most robust implementation plan will fail to drive the desired results without impactful use cases.

Next, business leaders must develop a long-term AI integration strategy. When implemented correctly, AI can help predict market shifts, adapt to changing customer preferences and optimise supply chains in various sectors. In finance, GenAI reshapes customer-centric services, simplifies tax preparation and provides effective digital assistants. In healthcare, it enhances personalised care and accelerates drug discovery and innovation.

One example of why this is especially important for specific industries comes from a leading biotech company that successfully embedded generative AI tools across its operations, leading to accelerated development processes and improved efficiency. The company used over 100 generative AI solutions to reduce the time required to develop new vaccines significantly. These results no doubt required thoughtful planning and implementation.

Aside from tangible business results, leaders must also focus on how a strong AI plan can unlock potential with employees. By building trust with ongoing communications and robust training, organisations can assure employees that they are included in the transformation journey. Employees are eager to join in — Unisys research reveals that 79% of employees feel that gaining AI skills will accelerate their career development. This optimism rings true with employees currently using AI, with 71% reporting enhanced job satisfaction thanks to the technology.

Mechanisms for Strategic Implementation

So, what does strategic implementation look like in practice? There are a few crucial steps to follow before deployment:

1. Data Preparation: First, organisations must collect, clean and structure data to optimise it for AI algorithms. This involves taking inventory of data sources and documenting formats, structures and storage locations to remove outdated, inaccurate data that could impede AI outputs.
2. Data Governance: Businesses must establish robust policies to maintain data quality, including validation rules, data archiving protocols and ongoing monitoring.
3. IT Infrastructure: Next, leaders should allocate additional resources to IT infrastructures to ensure the smooth integration of AI solutions.
4. Training Staff: Organisations must also direct resources to train staff and help employees use AI effectively and responsibly. Employees need comprehensive training and a collaborative environment to share and develop best practices.
5. Ongoing measurement: Enterprises should identify and measure success metrics to ensure continued alignment with business goals.

Successful AI implementation requires a strategic approach prioritising business objectives, clear metrics, comprehensive training, and meticulous data management. By looking at your existing data, cleansing it, and securing it, businesses can ensure the integrity and reliability of their AI systems. As businesses continue to navigate the digital landscape, those that invest in strategic AI implementation will be well-positioned to drive innovation and achieve long-term success. With this methodology, even the most highly regulated organisations can harness GenAI’s transformative power to revolutionise their operations and set themselves apart.