From adoption to value creation – how to unlock the full potential of Gen-AI

Generative AI (Gen-AI) is already demonstrating its ability to drive significant individual productivity gains. As employees are freed from repetitive tasks, they have been able to dedicate more time and energy to higher-value activities requiring creativity, critical thinking and human interaction. Yet the true transformative potential of Gen-AI extends far beyond individual productivity gains, showing the potential to deliver a range of benefits to organisations through the creation of new products, services and business models previously unimagined, by providing access to real-time data analysis to empower leaders to make more informed and strategic decisions, allowing organisations to automate new processes, adapt to changing market conditions more efficiently and respond to customer needs with greater speed and agility.

By embracing a strategic approach focusing on the union of technology and human capability, organisations can harness the transformative power of Gen-AI and unlock unprecedented levels of productivity, innovation, and growth. The key, though, lies in recognising that Gen-AI is not a replacement for human intelligence but rather a powerful tool that, when wielded effectively, can augment and amplify our uniquely human capabilities, propelling us towards a future where human potential and technological innovation work hand-in-hand to create a more prosperous and fulfilling world.

The successful adoption of Gen-AI will also demand a strategic, top-down approach to implementation, beginning with active leadership from the CEO and their senior management. This article – the first in a five-part series – outlines the necessary steps required to achieve successful adoption, focusing on the pivotal interaction between technology, leadership, safeguards and processes required to deliver Gen-AI value, informed by insights from the deployment of Deloitte’s own proprietary Gen-AI solution, PairD¹.

The pivotal role of the leadership

Successful implementations start at the top, and CEOs and leadership teams both have a critical role to play in the Gen-AI journeys of their organisations, moving beyond basic technology awareness towards a more tech-savvy footing. To fully harness the power of Gen-AI, leaders must also shift their focus from simple approvals to proactive participation, ensuring AI is integrated into their institution’s broader business goals. This includes:

• Engaging in hands-on learning: through participation in AI workshops, simulations and conferences to foster a deeper personal understanding of AI capabilities and risks.
• Forging strategic partnerships: collaborating with technology startups, their venture backers and the ‘BigTech’ giants to access and leverage expertise across the AI ecosystem.
• Championing responsible AI development: ensuring that AI initiatives prioritise transparency, fairness, ethics and accountability to build trust both within the organisation as well as with customers, regulators and the market.
• Implementing robust governance: leading on the establishment of AI governance structures, including ethics boards and audits, to ensure ongoing compliance, adhering to regulatory changes and ethical AI use.

Our own experiences with the deployment of PairD underline the critical role that leadership plays in supporting user adoption, with visible support and active usage by senior leaders emerging as a critical driver of adoption. Where leadership actively championed PairD and integrated it into their workflows, adoption rates were significantly higher.

Moving beyond point solutions

While initial Gen-AI projects often focus on solving isolated challenges, true transformation comes from rethinking established business processes. This is the critical effort into which leadership energy and engagement can most usefully be channelled. Instead of automating individual tasks, organisations need the courage and vision to embrace a multi-modal approach, reimagining whole workflows to truly maximise the benefits of Gen-AI to their organisations. To do this successfully, firms will need to engage in a set of coordinated motions, including:

• Adopting an iterative approach: begin with small pilot AI programs that assist humans in areas like customer service. This will help them acquire early wins to showcase progress. Over time, the autonomy of AI can be increased based on real-world feedback, with a phased approach building confidence and allowing organisations to refine processes as they go to ensure they maintain their alignment with the goals of the business.
• Leveraging the multi-modal capabilities of Gen-AI: the opportunity presented by Gen-AI goes far beyond next-gen chatbots, and a successful strategy will encompass its ability to integrate with other technologies. For example, consider a traditional claims processing system, which typically involves manual data entry, document review and customer interactions across different departments. By leveraging Gen AI's multi-modal capabilities, the entire process can be streamlined, with OCR² data extraction to make lighter work of forms, NLP³ to analyse claim documentation and Conversational AI to interact with customers, providing updates and gathering information. In this way, the multi-modal capabilities of Gen-AI can be used to eliminate bottlenecks, reduce errors, free up precious resources and significantly improve the customer experience.
• Measuring impact holistically: at every stage of the process, firms need to take time to evaluate the success of their Gen-AI implementations, basing their assessment not just on cost savings but also on customer experience feedback, process efficiency and risk mitigation. For example, a Gen AI-powered marketing campaign could move beyond simple click-through rates to offer sentiment analysis based on customer responses, efficiency gains in the creation of content as well as an overall reduction in manual targeting errors.

Reimagining end-to-end processes is an essential requirement for unlocking the full value of Gen-AI. At Deloitte, the design of PairD focused on simplifying user experiences by minimising feature complexity and streamlining workflows. This human-centred approach was crucial for driving adoption, particularly in an enterprise setting where different teams had varied needs.

Humanising the AI experience

As AI becomes more integrated into the operations of financial services, ensuring trust and transparency likewise becomes ever more important. Human-centred design principles can help in bridging the gap between complex AI systems and the humans who rely on them. In particular, there are several human-centred design concepts that institutions should consider as part of their own Gen-AI journeys:

• Contextual, intuitive interfaces: design systems that provide full context for their outputs, making them easier for users to interpret and act upon. For example, integrated Gen-AI-powered visual tools can be used to help creative marketing teams explore customer sentiment analysis more effectively, enabling them to explore interactive graphs mapping customer feedback to specific product features to reveal the ‘why?’ behind the numbers.
• Feedback loops and ‘human-in-the-loop’: ensure users can provide feedback on AI outputs dynamically, integrating mechanisms that capture feedback on the quality of generated inferences, flag inaccuracies and biases and recommend areas for improvement. This feedback can then be used to retrain and refine the LLM in a process of constant improvement.
• Empathy-driven design: also, develop AI solutions based on user’s needs and experiences to identify potential ethical dilemmas earlier in the cycle. This will ensure fairness, transparency and trust are inbuilt by design. For example, conducting thorough user research before deploying a Gen-AI solution will ensure needs, pain points and expectations are well understood early on. Mapping user journeys can also help to identify potential areas where a solution might fall short or create unintended consequences. Conversely, it is also important to proactively anticipate potential biases or ethical dilemmas before they arise. Integrating mechanisms that permit users to challenge generated inferences are another way organisations can ensure that human values and ethical considerations remain central in their Gen-AI journey.

For institutions, designing your Gen-AI solutions with the user in mind is great way to foster trust and transparency from the outset. Deloitte recognised early on that user experience would be paramount to PairD's success. A simplified UI/UX, inspired by mobile-first principles, proved highly effective. Pairing down features, streamlining user journeys, and minimising menu navigation further enhanced usability, driving user adoption.

Accelerating adoption through the ‘three Es’ – Education, Empowerment and Early wins

A key barrier to the successful adoption of Gen-AI for institutions can be the hesitation of business leaders, who may be uncertain about its risks and returns. Overcoming reluctance requires a combination of education and empowerment, as well as the ability to demonstrate early successes. Useful strategies for driving stronger Gen-AI adoption include:

• Educating and empowering leadership: running executive workshops to demonstrate the potential of Gen-AI to deliver lower costs, higher revenues and improved customer experiences, backed by relevant, real-world financial services success stories, will help lock in support for programmes.
• Leveraging enabling functions to showcase quick wins: focusing initial Gen-AI projects on internal process improvements, such as automating invoice processing in the Finance department, can demonstrate immediate cost savings and efficiency gains. This success can then be leveraged to secure buy-in for more ambitious Gen-AI initiatives in customer-facing areas.

In rolling PairD out to the wider business, Deloitte discovered that overwhelming users with generic training materials was also counterproductive. Instead, short, role-specific videos demonstrating practical applications of the system within specific job functions proved far more effective. Embedding formal training modules into the organisation's learning platform further streamlined access and also allowed for the tracking of training completion.

Gen-AI as a catalyst for transformation

Gen-AI is not just a tool for automating tasks. It is a catalyst for transformation at both the individual and organisational levels. Much of the value of Gen-AI lies in its ability to enhance human productivity and creativity while driving new business models and decision-making processes. The challenge for organisations then is to harness the transformation benefits of Gen-AI. We recommend the following steps:

• Targeting seamless integration: by embedding Gen-AI into existing workflows, institutions will augment rather than disrupt their processes. Imagine, for example, a legal team tasked with researching precedents for a complex case. Normally, this would involve hours of sifting through databases and documents. By integrating Gen-AI into their workflow, the team significantly reduces time spent on ‘busy work’, speeding up analysis of legal data and the identification of relevant precedents. In this scenario, time saved can also be farmed back into value-added activity such as case strategy, client interaction and the development of legal arguments.
• Empowering human expertise: focus too on developing human skills like critical thinking, emotional intelligence and ethical judgment. All of these will only become even more valuable in an increasingly AI-driven world.
• Embracing organisational agility: when transformation is successful, Gen-AI can enable faster responses to market changes and create new business opportunities. Ensure your workforce is engaged and ready for this step-change in capability.

A human-centric approach to Gen-AI

Of course, any discussion around the human component of the Gen-AI journey must also address how to manage the nervousness that some employees feel concerning the threat of AI replacing human jobs. A human-centric approach to Gen-AI adoption focuses on using AI to augment, not to replace, human expertise. By automating tedious manual tasks, Gen-AI allows employees to focus on higher-value activities – such as strategic decision-making and customer interactions – boosting efficiency, effectiveness and the quality of outputs.

However, while Gen-AI excels at automating tasks, it is the uniquely human skills of users that will become even more valuable in this new landscape. As Figure 1 below illustrates, we should think of this as a partnership between human and ‘robot’.

Source: Deloitte experience

In some of these examples, we can also see how a lack of human intervention will render it impossible for Gen-AI programmes to succeed. Hence, a truly human-centric approach to Gen-AI is vital, and should include the following elements:

• Using Gen-AI as a ‘co-pilot’: position these tools in ways that enhance human expertise, freeing up time for more valuable critical thinking and strategy-based tasks.
• Democratising AI: provide employees with tools they can use to customise and control Gen-AI solutions, empowering them to create prompts and agents tailored to their needs.
• Build trust through transparency: invest in the transparency of AI systems, giving employees and customers confidence in AI-driven decisions by clearly explaining how these systems work, incorporating human oversight into critical decision-making steps.

The potential for Gen-AI to transform financial services is vast, but realising its full potential will require a shift in leadership mindset as well as organisational approach. The successful adoption of AI hinges on active leadership, the reimagination of business processes, and a focus on augmenting human intelligence rather than merely replacing it. CEOs must therefore take a central role in driving AI deployment, leading from the top and embedding AI into the core of their business strategy.

At Deloitte, our deployment of PairD demonstrated how critical the involvement of senior leadership was for the success of AI initiatives. CEOs cannot afford to delegate AI entirely to their CIOs or IT teams. Instead, they need to engage deeply with AI’s capabilities and risks, ensuring the technology aligns with their long-term business goals. In PairD’s case, by articulating a clear vision for Gen-AI integration and championing its benefits, the active participation of senior leaders boosted adoption rates across the organisation, fostering trust and engagement at all levels of the business.

Beyond leadership, organisations must also move away from piecemeal AI solutions and think more holistically. Gen-AI should be used to reimagine end-to-end processes, improving efficiency and customer experience while opening new avenues for innovation. PairD’s success hinges on its user-centric design, which both simplified processes and made AI-driven workflows accessible to all employees, regardless of technical proficiency. This approach ensured that the tool was not only effective but also widely adopted, enabling Deloitte to maximise the value of AI integration.

Ultimately, Gen-AI is about more than the technology alone – it is as a tool for amplifying human potential. To unlock its full value, organisations need to invest in continuous learning, human-centred design, and leadership-driven strategies that ensure AI enhances, rather than replaces, human intelligence. By following these principles, financial institutions can harness AI to deliver lasting value. However, this must be done in a risk sensitive way rooted in privacy protection, security and good governance. In our next article, we look at how a ‘safety first’ approach to Gen-AI adoption need not limit its benefits.

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References:

¹ Developed by Deloitte’s AI Institute, PairD is an internal Generative AI platform designed to help the firm’s people with day-to-day tasks, including drafting content, writing code and carrying out research safely and securely. The tool is also able to create project plans, give project management best practice advice and suggest task prioritisation.

² OCR = Optical Character Recognition

³ NLP = Natural Language Processing