How can organisations harness the power of generative AI to work not only faster but also smarter? This question was central to a new study by the World Economic Forum, led by Marlene de Koning of PwC. The report focused on the ways companies worldwide are using GenAI to transform workplaces and provides a detailed blueprint for organisations looking to scale from simple GenAI applications to an integrated, strategic approach.
Marlene de Koning, a specialist in HR technology, data, and GenAI, interviewed more than twenty international companies leading the way in GenAI adoption for this study.
The promise of GenAI
Generative AI can make organisations more efficient and smarter, with the potential to restructure processes and increase productivity. Erin Otten, a PwC specialist in cloud and AI, emphasises that the value of AI lies in rethinking how your organisation works. However, many companies get stuck at the initial 'quick wins', failing to realise the full potential of GenAI. According to the World Economic Forum report, GenAI is developing rapidly and will be fully integrated into business processes within five years. This brings new opportunities and responsibilities. Ethical issues around bias and privacy are becoming more important, and executives need to increase their data literacy to work effectively with GenAI-generated insights.
The five pillars for success
How do you grow towards strategic impact and GenAI maturity? De Koning and Otten identify five pillars as the foundation for successful scaling of GenAI:
1. Trust and ethics as a foundation
Companies are often hesitant with artificial intelligence (AI) due to concerns about errors and compliance. This leads to distrust: AI errors are weighed more heavily than human errors ('death by AI'). To make GenAI initiatives successful, organisations must build trust and actively involve employees in the transformation. Only then can the full value of GenAI be realised. 'Without trust, the technology remains unused,' warns De Koning. 'Employees need to know that GenAI supports them and does not replace them.'
Additionally, ethical considerations are becoming increasingly important. Bias in algorithms, data leaks, and lack of transparency can lead to resistance within organisations. Therefore, PwC advocates for clear ethical guidelines and actively involving employees in the implementation of GenAI.
2. Cloud and data: foundation for AI acceleration
Quality and well-managed data are crucial for successful generative AI, but organisations often underestimate the complexity of this. 'Getting data in order may not be attractive, but it is absolutely essential for scalable impact,' says Otten. A solid data strategy, supported by governance, security, and compliance, is necessary. The cloud plays a key role in uniting data, services, and communication, providing the infrastructure and scalability for AI models. Platforms like Microsoft Azure support this. Otten: 'With a strong cloud and data structure, organisations can leverage generative AI more quickly.' De Koning adds: 'Without this foundation, results remain limited to experiments.' However, organisations can start with available 'use cases' to create immediate value. Additionally, a culture of digital and data literacy is crucial for success with GenAI, emphasises De Koning.
3. Strategic leadership and an innovative culture
GenAI adoption is not just a technological issue but also requires a fundamental cultural change within organisations. Leadership plays a key role in this. 'The board must understand how GenAI works and have a vision of how this technology adds value to the business strategy,' says De Koning.
Encouraging a culture where experimentation and learning are promoted is essential, according to Otten. 'Employees need to feel they have the space to experiment with new technologies without being punished for failure.' PwC advises organisations to develop leadership programmes where executives learn how to effectively use GenAI while inspiring their teams to engage with this technology.
4. Strategic integration: embedding GenAI in the core
A common pitfall in GenAI implementations is treating them as standalone projects. This limits the impact of GenAI on business operations. Otten: 'The power of GenAI lies in its integration with core processes, such as supply chain, marketing, or finance.'
While GenAI plays an important role, it is only part of a broader technological palette. 'Companies must first prioritise their strategic goals and then determine which combination of techniques, including GenAI, is needed to achieve these goals,' emphasises Otten. 'Technology is not the goal, but a means to support business objectives.'
Strong examples of GenAI can be found in knowledge-intensive sectors and customer contact centres. This shows that GenAI not only promotes operational efficiency but also increases customer value and enables innovation and scalability.
5. Measuring and optimising
According to the experts, every successful GenAI initiative starts with a clear 'value case'. 'It is important to sharpen your strategic goals: what do you want to achieve and how can GenAI and other solutions contribute to this?' says Otten. 'Define clear KPIs, such as cost savings, productivity, customer satisfaction, and efficiency gains, and measure the impact from the start.'
A well-functioning solution alone is not enough. The challenge lies in realising and demonstrating value. 'You cannot achieve success without measuring what works and what doesn't,' emphasises De Koning. To prevent organisations from being disappointed in the promise of GenAI, concrete measurement tools are essential to work iteratively and achieve scalable results.
From experiment to scaling
De Koning and Otten combine insights from client projects with their own practical experience: PwC also explores many of the new possibilities as 'client zero' and tests them in its own practice and organisation. Embarking on a journey with rapidly changing technology requires the courage to make mistakes, and on the GenAI journey, knowledge gives way to joint exploration. An example is an eight-week programme for M365 Copilot implementation, where companies experiment with GenAI applications and analyse results directly. 'This approach lowers the threshold to really get started,' says De Koning. PwC also focuses on training and education, making GenAI widely accessible within organisations and involving employees, which accelerates and strengthens adoption.
Conclusion: GenAI as a catalyst
Generative AI offers companies unprecedented opportunities to work not only faster and more efficiently but also to enter new markets and increase customer value. This success does not come automatically; it requires strategic investments, courage, and vision. But if executed well, the reward is commensurate, concludes Otten: 'Companies that dare to innovate benefit not only from efficiency but also have the chance to become leaders in their sector.'
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