Ethical AI programs should be viewed as an investment, with clear economic and reputational returns, as opposed to compliance-driven cost centers. Deloitte’s Second Annual Ethical Technology Report found that leaders who define trustworthy and ethical principles for emerging technologies create social, reputational, and financial value for their organizations.
According to the report, the percentage of organizations who cited the importance of “Responsible” AI increased by 50% from 2022 to 2023. Business that cited “Fair & Impartial” also increased year-over-year.
Here are a few ways to think about the returns on an organization’s investment in ethical AI.
Poor AI Outcomes Impact Revenue
By 2025, machines are expected to handle over 50% of workplace tasks (World Economic Forum), but the risks of biased algorithms and ethical lapses can result in significant consequences like financial losses, reputational damage, and legal challenges.
Quoting a 2023 Thomson Reuters whitepaper, “If individuals from certain intersectional demographic groups are underrepresented in the data upon which AI systems are trained, the AI might perform disproportionately worse when applied to these groups.”
Biased data is not the strongest or most accurate data; it can cause down-the-line impact on product accuracy, customer experience, and ultimately, revenue. Conversely, more accurate data is more actionable, leading to improved accuracy, customer loyalty, and revenue over time.
Speaking to Forbes, Claire Cheng, senior director of AI engineering at Salesforce, rightfully argues that with increased AI adoption must come education and solutions aimed at recognizing and mitigating AI’s limitations and biases.
Ethical AI to Mitigate Financial & Reputational Risk
Privacy and bias are naturally counterforces. On the one hand, privacy is fundamental and requires data minimization. On the other hand, to truly combat bias, you fundamentally require detailed information to understand the issue. Privacy and data have been at the forefront of many hefty fines, especially when companies start to use users’ biometric data without informed consent. Within healthcare, there are even more regulations around PII, HIPAA, and standard privacy laws that pack a hefty financial fine if used inappropriately.
If patients knew that companies were either selling their personal health information or using it for AI without the patient’s consent — what could be the impact? What if you were the patient? Ethical missteps can have negative impacts across many aspects of a company.
Source: Deloitte’s Second Annual Ethical Technology Report
An Evolving Regulatory Landscape
The regulatory landscape surrounding AI is evolving rapidly, with organizations like UNESCO and the Responsible AI Institute producing recommendations on the ethics of AI integration throughout its lifecycle.
A specific area that will increase in “regulatory relevance” is the auditing of AI risk, bias, and fairness, according to Thomson Reuters. This same report notes that similar to standardized cybersecurity audits, AI auditing will emerge as a new arena — and will increasingly lean on third-party AI auditing tools.
Business leaders are rallying around the importance of regulatory frameworks: KPMG found that 81% of CEOs are concerned that the lack of regulations for generative AI in their industry will hinder their organizations’ success.
A Framework for Measuring the ROI of Ethical AI
Given the nuanced impacts of AI, the way organizations would typically assess ROI on technological investments doesn’t necessarily translate to tools and systems that ensure ethical AI. With ethical AI, there can be both economic impact and intangible returns, as mapped out by the IBM Institute and the University of Notre Dame.
Per their findings, the alignment of ethical considerations and financial priorities becomes clearer when outlined against the different layers of potential business impact:
- Traditional ROI: Revenue generation and cost avoidance
- Intangible ROI: Reputational impact
- Capabilities ROI: Defined as an improvement in knowledge, skills or expertise at an organizational level which serves to make the business more sustainable in the long-term
These factors outline why investing in the personnel, tools, and systems to move from ethical AI in principle to ethical AI in practice just makes good business sense. It’s no wonder there has been a marked rise in ethical AI startups (like Destined AI) alongside the growth of the industry overall.
Source: EAIDB (Ethical AI Company Database)
Ultimately, ethical AI is not just a moral imperative; it’s a sound business decision with a measurable and substantial return on investment.
Sources:
- Deloitte, “Second Annual Ethical Technology Report” (2023)
- Forbes, “Why Ethical And Responsible AI Is Our Most Important Investment” (2023)
- Forbes, “Workplace Misconduct Cost U.S. Businesses $20 Billion in Past Year: New Study” (2021)
- IBM Institute and University of Notre Dame, “Return on AI Ethics: A Holistic Framework“
- Sage Journals, “Four Investment Areas for Ethical AI” (2021)
- Thomson Reuters, “Addressing Bias in AI” (2023)
- Unesco, “Ethics of Artificial Intelligence” (2024)