Accelerating the future: the transformations of health and wealth services and pharma’s commercial activities

This week we have published the seventh and eight predictions from our Accelerating the future: Life Sciences and Healthcare predictions 2030 report, ‘The convergence of health, wealth and longevity services’ and the ‘End-to-end transformation of pharma’s commercial activities’. Our seventh prediction explores how governments, employers and technology providers are collaborating to address the challenges of ageing populations and promote longer, healthier and more economically active lives. The eight prediction focuses on the digital transformation the pharma commercial function will undergo until 2030, leveraging AI and data-driven insights to optimise commercial operations, enhance customer engagement and improve patient outcomes. Our blog this week highlights the key insights in these two predictions.

Collaborating to build a resilient economy

By 2030, governments are adapting to the opportunities and challenges of ageing populations and declining birth rates by implementing policies to tackle economic inactivity (see figure 1). This includes providing universal equitable health coverage, decent work for all and sustained flexible retirement options, and increased collaboration with healthcare providers, employers, and technology companies to keep people healthier and economically active for longer. These partnerships leverage data and technology to improve population health, enhance financial well-being, and create a more sustainable model for ageing societies.

This shift also involves a greater focus on preventative care and well-being initiatives that empower individuals to maintain their health, reducing reliance on reactive healthcare and boosting workforce productivity. Employers’ role in promoting health and well-being is already becoming increasingly recognised, as reflected by 2024’s World Mental Health Day theme, ‘Mental Health at Work’. Celebrated on 10 October, it recognises the vital connection between working conditions, mental health and productivity. By 2030, employers are crucial in this transformation, fostering inclusive work environments, including through continuous learning, flexible working, fluid careers, and the creation of multigenerational work teams. Moreover, they support employees' holistic well-being by proactively identifying risks, such as burnout, and creating wellness strategies to mitigate these risks.

Simultaneously, platform-based technologies and data analytics are revolutionising insurance and pension models, enabling personalised solutions and improved outcomes. This collaborative approach, encompassing governments, businesses, communities, and individuals, aims to create a more sustainable and equitable health system for all ages, and a more productive and resilience economy.

Figure 1. The wider benefits to population health from improved employee health and well-being

Source: Deloitte analysis.

To realise this future, stakeholders will need to overcome key constraints to create a more age-inclusive and sustainable health ecosystem. By 2030, investments in upskilling, retraining and educational programmes have addressed the demand for health, digital and financial literacy. Innovative funding models and value-based insurance designs promote preventative care and incentivise healthier lifestyles. Robust regulations ensure consumer protection against discrimination and fraud, data privacy, and equitable access to services. And, finally, secure interoperable platforms storing data on claims, clinical history, financial health and social needs, underpinned by advanced cybersecurity, enable data-driven insights while maintaining individual trust.

How can GenAI accelerate this future?

While the banking and fintech sectors currently lead in AI adoption, the insurance and wealth management industries are rapidly catching up, recognising AI's potential to address health, wealth, and longevity challenges. AI can revolutionise client engagement, personalise wellness programs, and provide holistic health insights by integrating diverse datasets. Furthermore, AI-powered tools can empower individuals with personalised health recommendations, informed long-term financial planning, and increased social connectivity, ultimately promoting independence, well-being, and a higher quality of life as they age. However, mitigating ageism risks through inclusive design and diverse data representation remains crucial to ensure equitable access and benefits for all.

Customer-centric, platform based commercial models

By 2030, the commercial function of pharma companies has undergone a complete digital transformation, integrating AI across its operations to enhance efficiency, cost-effectiveness, and customer experience (see Figure 2). This shift includes leveraging AI-powered data platforms and customer relationship management (CRM) systems, enabling data-driven decision-making and personalised engagement with healthcare professionals (HCPs) and patients. By integrating internal and external data, including real-world data (RWD), companies gain a holistic view of customer needs and behaviours, facilitating targeted omnichannel campaigns, personalised messaging, and optimised resource allocation. This results in improved engagement, faster time-to-value, and stronger customer relationships.

Automation plays a key role in enhancing the customer experience by streamlining processes such as order management and account management, reducing errors and delays. The use of digital twins to simulate market dynamics and patient behaviours allows for more effective planning and resource allocation, ultimately driving better outcomes for both the company and the patients it serves.

Figure 2. The ‘string-of-pearls’ approach to commercial strings together multiple use-cases to transform the entire process

Source: Deloitte analysis.

To succeed in achieving our vision of the future, pharmaceutical companies will address key constraints related to skills, funding, regulation, and data management. By 2030, they have invested in upskilling their workforce, fostering a culture of agility and innovation. Data-driven incentive structures, coupled with flexible pricing models, optimise resource allocation and demonstrate value. Robust compliance measures, powered by advanced analytics, ensure patient privacy and ethical practices. By harnessing cutting-edge data analytics and establishing secure, interoperable platforms, companies can leverage the full potential of data-driven insights while maintaining transparency and trust.

How can GenAI accelerate this future?

AI presents a significant opportunity to unlock substantial value across pharma’s commercial operations. Deloitte estimates that a top biopharma company could capture US$5-7 billion in value over five years by scaling AI adoption, with the commercial function realising 35 per cent of this value. For instance, AI can analyse patient profiles and online behaviours to personalise marketing messages, optimise ad spending, and predict customer behaviour for more effective sales strategies. Furthermore, AI can streamline order management, optimise inventory, and enhance pharmacovigilance by analysing vast datasets to identify potential safety signals more efficiently.

Beyond these operational improvements, AI can revolutionise patient support programs (PSPs) by enabling personalised interventions and risk management strategies. By analysing data from electronic health records, social media, and adverse event reporting systems, AI can identify individuals at higher risk of experiencing adverse events, allowing for proactive intervention and tailored support. This personalised approach can lead to better adherence to treatment plans and improved health outcomes for patients. Overall, AI empowers biopharmaceutical companies to transition from traditional, reactive models to proactive, data-driven approaches that enhance efficiency, reduce costs, and ultimately improve patient care.

Conclusion

The health-wealth services and pharma’s commercial activities are going through profound changes. A convergence of AI, data analytics, and collaborative ecosystems are crucial enablers for this transformation in both sectors, albeit with distinct applications. In the first case, we see a convergence of stakeholders to provide integrated services, preventative care, and empower individuals to manage their health and financial well-being as they age. The rise of AgeTech signifies a proactive approach to longevity, supported by personalised solutions. Meanwhile, the pharmaceutical industry is embracing a customer-centric model, leveraging AI for targeted engagement, personalised medicine, and enhanced patient support. This data-driven transformation promises to enhance efficiency, reduce costs, and ultimately improve patient care. In both, consumer-centricity is key.