Ethics & Policy
The New Frontier of Corporate Governance

As artificial intelligence-based solutions gain ground in the corporate sphere, so too does the conversation around their responsible implementation. Beyond technological progress, the focus today is on how companies are integrating these developments from an ethical, transparent, and governance-aligned perspective.
This means organizations face a strategic challenge: It is not enough to adopt AI, it must be implemented responsibly, particularly in industries that manage sensitive data and operate under growing regulatory pressure.
While 73% of companies in North America plan to expand AI use, only 58% have assessed its legal or ethical risks. This exposes a critical tension, as innovation without responsibility jeopardizes both trust and business resilience. In Mexico, the situation reflects an overall lag, with many organizations still in pilot phases and lacking formal governance frameworks.
A recent report highlights that 95% of organizations already using AI lack structured governance models. Even more concerning, only 8% have mature, fully integrated practices, while the majority rely on fragmented or entirely absent approaches.
The OECD has also warned of technical, organizational, and cultural barriers to implementing sustainable AI in Latin America, emphasizing the lack of formal risk management programs and the limited involvement of compliance and legal departments.
In practice, this means AI continues to be deployed in isolated use cases, without integration into long-term strategies. Despite its vast potential, AI is still too often confined to task automation or process optimization, rather than being embraced as a strategic pillar. This gap, however, represents a major opportunity for companies aiming to differentiate themselves and deliver stronger results.
Emerging Regulatory Efforts in Latin America
Not all is bleak. In Latin America, some regulatory efforts are emerging to close the gap. In Brazil, for instance, draft legislation aims to incentivize risk assessments and classify “high-risk” AI systems. Meanwhile, in Mexico, initiatives such as working groups led by the Mexican Center for Artificial Intelligence (CENIA) are exploring ethical standards for AI.
Yet, adoption is moving slowly compared to the pace at which businesses are deploying AI to process massive volumes of personal and corporate data. The advent of generative AI, fueled by technologies like ChatGPT, has brought new challenges, placing organizations on a spectrum that ranges from excessive optimism — believing AI will solve every problem — to cautious resistance, fearing job displacement.
In this context, finding a balanced approach is essential, helping companies align expectations toward strategic and realistic adoption. This, in turn, requires strengthening internal security policies that include multifactor authentication, periodic audits, and full data traceability. Such measures are particularly crucial in sensitive sectors such as finance, healthcare, and government.
What do ethics and governance mean for businesses?
Risk assessment and data traceability: Essential for periodic audits and mapping corporate data flows.
Security: Multifactor authentication, access control, and anonymization are key practices for protecting confidentiality and ensuring ethical data handling.
Transparency and explainability: AI models must be interpretable and well-documented, especially in automated decision-making scenarios. This strengthens legitimacy and allows auditing of internal mechanisms from early stages.
Bias mitigation: Through technical safeguards and explicit policies to ensure fairness across systems.
Cross-organizational governance: Oversight must be embedded throughout the enterprise, not siloed within technical departments. Some models connect governance from a macro perspective down to individual AI systems.
Education and internal culture: Vital to prevent informal or unregulated AI use by employees, which can create significant risks: hidden AI usage, unsupervised errors, and exposure of corporate data to external platforms, among others. Ethical and operational AI literacy is as important as technology selection itself.
AI represents one of the most significant technological transformations for enterprises in the 21st century. But adoption without an ethical compass can evolve into a systemic risk. Ethics and governance are not obstacles to innovation, they are the foundations that ensure innovation is sustainable, trustworthy, and socially accepted.
For many organizations in Mexico, particularly those in complex, highly regulated industries, building an internal governance architecture from scratch may seem overwhelming. After all, adopting AI goes far beyond implementing a new technology. It requires striking a balance between two extremes: companies that expect AI to solve everything, and those that resist adoption out of fear of automation and job loss.
On this journey, having strategic partners can make a critical difference. Partners that not only understand the technology, but also bring expertise in international regulatory frameworks and can design governance structures adapted to the local context, particularly in environments where regulations evolve rapidly and where the talent gap in responsible AI remains significant.
Digital transformation is not just about adopting tools; it is about redefining how companies perceive their impact on customers, employees, and society at large. That is why, when implementing AI, every organization must ask itself: Are we building solutions that are not only useful, but also fair? Do we have mechanisms in place to prevent unintended collateral damage? And are we partnering with the right allies to navigate this path with awareness, transparency, and long-term vision?
Ethics and governance are not the final destination of artificial intelligence. But they are indeed the vehicle that ensures the journey is worth taking.
Sources:
PwC (2024).
Compliance Week/GAN (feb 2025).
Brazil’s AI Legal Framework (PL 21/2020)
Ethics & Policy
Hyderabad: Dr. Pritam Singh Foundation hosts AI and ethics round table at Tech Mahindra

The Dr. Pritam Singh Foundation and IILM University hosted a Round Table on “Human at Core: AI, Ethics, and the Future” in Hyderabad. Leaders and academics discussed leveraging AI for inclusive growth while maintaining ethics, inclusivity, and human-centric technology.
Published Date – 30 August 2025, 12:57 PM
Hyderabad: The Dr. Pritam Singh Foundation, in collaboration with IILM University, hosted a high-level Round Table Discussion on “Human at Core: AI, Ethics, and the Future” at Tech Mahindra, Cyberabad.
The event, held in memory of the late Dr. Pritam Singh, pioneering academic, visionary leader, and architect of transformative management education in India, brought together policymakers, business leaders, and academics to explore how India can harness artificial intelligence (AI) while safeguarding ethics, inclusivity, and human values.
In his keynote address, Padmanabhaiah Kantipudi, IAS (Retd.), Chairman of the Administrative Staff College of India (ASCI),
paid tribute to Dr. Pritam Singh, describing him as a nation-builder who bridged academia, business, and governance.
The Round Table theme, Leadership: AI, Ethics, and the Future, underscored India’s opportunity to leverage AI for inclusive growth across healthcare, agriculture, education, and fintech—while ensuring technology remains human-centric and trustworthy.
Ethics & Policy
AI ethics: Bridging the gap between public concern and global pursuit – Pennsylvania

(The Center Square) – Those who grew up in the 20th and 21st centuries have spent their lives in an environment saturated with cautionary tales about technology and human error, projections of ancient flood myths onto modern scenarios in which the hubris of our species brings our downfall.
They feature a point of no return, dubbed the “singularity” by Manhattan Project physicist John von Neumann, who suggested that technology would advance to a stage after which life as we know it would become unrecognizable.
Some say with the advent of artificial intelligence, that moment has come. And with it, a massive gap between public perception and the goals of both government and private industry. While states court data center development and tech investments, polling from Pew Research indicates Americans outside the industry have strong misgivings about AI.
In Pennsylvania, giants like Amazon and Microsoft have pledged to spend billions building the high-powered infrastructure required to enable the technology. Fostering this progress is a rare point of agreement between the state’s Democratic and Republican leadership, even bringing Gov. Josh Shapiro to the same event – if not the same stage – as President Donald Trump.
Pittsburgh is rebranding itself as the “global capital of physical AI,” leveraging its blue-collar manufacturing reputation and its prestigious academic research institutions to depict the perfect marriage of code and machine. Three Mile Island is rebranding itself as Crane Clean Energy Center, coming back online exclusively to power Microsoft AI services. Some legislators are eager to turn the lights back on fossil fuel-burning plants and even build new ones to generate the energy required to feed both AI and the everyday consumers already on the grid.
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At the federal level, Trump has revoked guardrails established under the Biden administration with an executive order entitled “Removing Barriers to American Leadership in Artificial Intelligence.” In July, the White House released its “AI Action Plan.”
The document reads, “We need to build and maintain vast AI infrastructure and the energy to power it. To do that, we will continue to reject radical climate dogma and bureaucratic red tape, as the Administration has done since Inauguration Day. Simply put, we need to ‘Build, Baby, Build!’”
To borrow an analogy from Shapiro’s favorite sport, it’s a full-court press, and there’s hardly a day that goes by that messaging from the state doesn’t tout the thrilling promise of the new AI era. Next week, Shapiro will be returning to Pittsburgh along with a wide array of luminaries to attend the AI Horizons summit in Bakery Square, a hub for established and developing tech companies.
According to leaders like Trump and Shapiro, the stakes could not be higher. It isn’t just a race for technological prowess — it’s an existential fight against China for control of the future itself. AI sits at the heart of innovation in fields like biotechnology, which promise to eradicate disease, address climate collapse, and revolutionize agriculture. It also sits at the heart of defense, an industry that thrives in Pennsylvania.
Yet, one area of overlap in which both everyday citizens and AI experts agree is that they want to see more government control and regulation of the technology. Already seeing the impacts of political deepfakes, algorithmic bias, and rogue chatbots, AI has far outpaced legislation, often to disastrous effect.
In an interview with The Center Square, Penn researcher Dr. Michael Kearns said that he’s less worried about autonomous machines becoming all-powerful than the challenges already posed by AI.
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Kearns spends his time creating mathematical models and writing about how to embed ethical human principles into machine code. He believes that in some areas like chatbots, progress may have reached a point where improvements appear incremental for the average user. He cites the most recent ChatGPT update as evidence.
“I think the harms that are already being demonstrated are much more worrisome,” said Kearns. “Demographic bias, chatbots hurling racist invectives because they were trained on racist material, privacy leaks.”
Kearns says that a major barrier to getting effective regulatory policy is incentivizing experts to leave behind engaging work in the field as researchers and lucrative roles in tech in order to work on policy. Without people who understand how the algorithms operate, it’s difficult to create “auditable” regulations, meaning there are clear tests to pass.
Kearns pointed to ISO 420001. This is an international standard that focuses on process rather than outcome to guide developers in creating ethical AI. He also noted that the market itself is a strong guide. When someone gets hurt or hurts someone else using AI, it’s bad for business, incentivizing companies to do their due diligence.
He also noted crossroads where two ethical issues intersect. For instance, companies are entrusted with their users’ personal data. If policing misuse of the product requires an invasion of privacy, like accessing information stored on the cloud, there’s only so much that can be done.
OpenAI recently announced that it is scanning user conversations for concerning statements and escalating them to human teams, who may contact authorities when deemed appropriate. For some, the idea of alerting the police to someone suffering from mental illness is a dangerous breech. Still, it demonstrates the calculated risks AI companies have to make when faced with reports of suicide, psychosis, and violence arising out of conversations with chatbots.
Kearns says that even with the imperative for self-regulation on AI companies, he expects there to be more stumbling blocks before real improvement is seen in the absence of regulation. He cites watchdogs like the investigative journalists at ProPublica who demonstrated machine bias against Black people in programs used to inform criminal sentencing in 2016.
Kearns noted that the “headline risk” is not the same as enforceable regulation and mainly applies to well-established companies. For the most part, a company with a household name has an investment in maintaining a positive reputation. For others just getting started or flying under the radar, however, public pressure can’t replace law.
One area of AI concern that has been widely explored in the media is the use of AI by those who make and enforce the law. Kearns said, for his part, he’s found “three-letter agencies” to be “among the most conservative of AI adopters just because of the stakes involved.
In Pennsylvania, AI is used by the state police force.
In an email to The Center Square, PSP Communications Director Myles Snyder wrote, “The Pennsylvania State Police, like many law enforcement agencies, utilizes various technologies to enhance public safety and support our mission. Some of these tools incorporate AI-driven capabilities. The Pennsylvania State Police carefully evaluates these tools to ensure they align with legal, ethical, and operational considerations.”
PSP was unwilling to discuss the specifics of those technologies.
AI is also used by the U.S. military and other militaries around the world, including those of Israel, Ukraine, and Russia, who are demonstrating a fundamental shift in the way war is conducted through technology.
In Gaza, the Lavender AI system was used to identify and target individuals connected with Hamas, allowing human agents to approve strikes with acceptable numbers of civilian casualties, according to Israeli intelligence officials who spoke to The Guardian on the matter. Analysis of AI use in Ukraine calls for a nuanced understanding of the way the technology is being used and ways in which it should be regulated by international bodies governing warfare in the future.
Then, there are the more ephemeral concerns. Along with the long-looming “jobpocalypse,” many fear that offloading our day-to-day lives into the hands of AI may deplete our sense of meaning. Students using AI may fail to learn. Workers using AI may feel purposeless. Relationships with or grounded in AI may lead to disconnection.
Kearns acknowledged that there would be disruption in the classroom and workplace to navigate but it would also provide opportunities for people who previously may not have been able to gain entrance into challenging fields.
As for outsourcing joy, he asked “If somebody comes along with a robot that can play better tennis than you and you love playing tennis, are you going to stop playing tennis?”
Ethics & Policy
“AI Ethics” Discourse Ignores Its Deadliest Use: War

AI Ethics is a hot topic in the artificial intelligence world. It features in keynote speeches at major conferences and spawns entire dedicated safety teams at large companies—all the while, government, industry and academic leaders make a point of how hard they’re working to make sure AI proceeds in an ethical way. Ostensibly, this is a response to well-founded fears about the technology’s possible (and proven) downsides, like its threat to the job market, or potential for harm in mental health settings.
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