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PwC's Guide to Responsible AI for Sustainable Business Growth

Artificial Intelligence has the potential to contribute an estimated $15.7 trillion to the global economy by 2030—a 14% increase in global GDP due to AI alone—according to research from PwC. This immense growth represents the most significant commercial opportunity in today’s fast-paced and competitive economy. AI is not just a tool for efficiency; it is a catalyst for innovation and transformation across various sectors. From healthcare and finance to education and logistics, AI is reshaping how businesses operate and how services are delivered, driving unprecedented levels of productivity and value creation.

AI's impact is evident in its ability to analyze massive datasets with remarkable speed and accuracy, uncovering insights that were previously unattainable. This capability is crucial as organizations face increasing pressure to adapt quickly to changing market conditions and consumer demands. Moreover, AI's resilience in automating complex processes ensures continuity and stability in operations, even amidst disruption.

It’s no longer a question of whether or not organizations should apply AI solutions. But rather, the discussion centers around how and where it should be applied. And what does it mean to practice ethical or responsible AI?

We sat down with AI and FinTech Director at PricewaterhouseCoopers (PwC), Michael Berns, to discuss how AI is being used for good to solve some of the world's most pressing issues, from financial crime prevention to rapid disease diagnostics and human trafficking intervention.

3 industry use cases of responsible AI in action

PwC plays a pivotal role in applying AI to drive digital transformation for its clients across various industries. As a global leader in professional services, PwC has a unique vantage point, integrating deep industry knowledge with cutting-edge AI technologies to solve complex business challenges. PwC assists organizations in harnessing AI to enhance operational efficiency, improve decision-making, and foster innovation.

The firm's commitment to responsible AI ensures that these solutions are not only effective but also ethical and transparent. PwC's position at the forefront of AI innovation allows it to explore and implement some of the most advanced and impactful use cases, providing unparalleled insights into the potential of AI to transform industries and create sustainable value. This expertise is showcased through three compelling use cases where AI is being harnessed for good: financial crime prevention, rapid disease diagnostics, and human trafficking intervention.

Financial crime prevention

AI and the financial sector are ideal bedfellows. AI technology such as Natural Language Processing (NLP) and predictive analytics have the capacity to transform customer engagement and workforce productivity for financial service providers. But the application of AI goes far beyond process automation.

Banks and other financial institutions are building AI solutions that assist in regulatory reporting and compliance—sometimes referred to as RegTech, or SupTech when employed by financial supervisory agencies. This entails the detection of anomalies in transactions or communications that point to potential threats like collusion, money laundering, front running, or other financial crimes. As this type of criminal activity grows increasingly advanced, the financial sector must keep pace and implement smarter mechanisms to accelerate risk detection and mitigation.

Use the ITONICS Radar to discover growth opportunities in the financial sector:

Rapid disease diagnostics 

With many global healthcare systems under economic and personnel pressure, any solution that saves time and resources has the potential to save lives. PwC cites the development of AI models that are able to identify connections between different complex sets of data and contextual information. Healthcare providers can use these insights to help inform their diagnoses and treatment plans.

Berns refers to this as a rare win-win-win situation. AI applications in healthcare enhance patient care, making it more personalized, targeted, and efficient. Hospitals can be better run and managed, with resources and capabilities optimized. “It’s very much an integrated solution that saves double-digit millions a year,” says Berns, emphasizing the economic impact of AI in healthcare.

Human trafficking intervention

Combatting human trafficking and exploitation has posed a challenge for governments worldwide. There is a lack of comprehensive and reliable data for anti-trafficking organizations to understand the scope of the problem, making it difficult to devise effective measures to identify and prevent trafficking.

This is where AI can assist. Similar to the software developed to help law enforcement agencies detect terrorism, NLP models can derive intent from communication in online forums, chat groups, and classified advertising websites. It pulls out patterns and profiles that suggest a possible exploitation case, allowing law enforcement to direct their focus for further investigation. Facial recognition technology is another AI-driven tool in the fight against human trafficking. It uses deep learning algorithms to match missing persons with online images showing victims of trafficking.

Berns has done previous work with Thorn, a tech-oriented anti-trafficking organization. Thorn uses AI solutions to help empower law enforcement, reducing the critical time spent searching for juvenile victims of trafficking by 60%—resulting in the identification of 9 children per day. “Over the last five years or so, more than 7,000 people were freed from human traffickers by using this solution,” shares Berns.

Addressing the artificial elephant in the room

The examples above exemplify a few of the ways that AI can be used to make the world a better, safer, and more just place. However, Berns, who admits he’s been referred to as an AI evangelist, knows that the adoption of AI is not without its problems.


While most business leaders claim they are interested in integrating AI solutions into their organizations, significant gaps in readiness remain. Businesses in China and the United States are generally much further ahead, heavily investing in AI tool development, adapting their processes to accommodate these technologies, and reskilling their workforces to effectively leverage AI capabilities. This proactive approach places them at a distinct competitive advantage.


The geographical disparity in terms of AI preparedness also gives rise to discussions of AI equity. If access to advanced technology like AI remains limited in low- and middle-income countries, the digital divide will continue to widen. This gap leaves these economies ill-equipped to compete globally, build resilience, and enhance capabilities within their workforces—all while exacerbating economic inequalities and stifling potential growth.

Data Privacy

Effective AI applications are highly dependent on a critical mass of data. Meanwhile, governments worldwide are progressively tightening regulations around the procurement and manipulation of data—especially where it is related to personally identifiable information (PII), such as in healthcare. Ensuring data compliance can be a lengthy process, and collectors of this data must clearly communicate their intentions, as well as the benefits of opting-in.


As with many new, disruptive technologies, societal tensions exist around the adoption of AI. There is a persistent fear that AI will bring about massive job losses. While it’s inevitable that AI will lead to the migration and, indeed, obsolescence of certain roles, Berns asserts that it will equally create opportunities for new roles within improved organizations. “If you get involved early as a country or company,” he advises, “then you will probably have a chance to be part of the disruption to create new roles rather than just being disrupted.”

So, does AI make the world a better place?

Berns would say unequivocally, “Yes, I strongly believe it does.” He admits, though, that AI is just a tool and is neither inherently good nor bad. Much like social media or the internet as a whole, it is how this tool is used that makes all the difference. 

Berns concludes, “Don’t be afraid of AI and disruptive technologies in general. They are here to stay; they’re not going anywhere.” And as AI becomes progressively ubiquitous in our lives, the mandate for responsible AI will only grow in importance. 

To gain strategic advantage, organizations must strive to be at the forefront of integrating bias-free algorithms and advanced machine learning into their processes. When these AI applications are configured to help deliver on an organization’s purpose—combining the best of machine intelligence and real human vision and empathy—this is where AI does good.

Infusing AI into innovation with the ITONICS Innovation OS

By infusing AI into the core of our innovation management software, the ITONICS Innovation OS enables organizations to leverage data and analytics to drive decisions, provoke action, and facilitate scalable, sustainable growth. Our AI-driven capabilities ensure that innovation leaders can spot the signals that matter and connect the dots between insights and R&D initiatives. This grounds innovation in real-world applications and fosters an environment for positive, perpetual progress. 

The Innovation OS seamlessly blends the power of AI with the potential of human ingenuity to strike a perfect balance between data-driven, bias-free decision-making and democratized innovation that invites diverse perspectives from all corners of your organization or network. This approach and ITONICS’s commitment to facilitating transparent end-to-end innovation ensure that your innovation efforts are aligned with organizational goals and deliver measurable and meaningful impact.



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