DelCreo, Inc.

Changing Legal Landscapes: M&A and AI

Weighing the Risks #14

Changing Legal Landscapes: M&A and AI

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Hi, enjoy this weeks curated risk and business updates.

The rapid growth of Artificial Intelligence technology in many different parts of a business is complicating contractual agreement with 3rd parties as well as mergers and acquisitions (M&A) transactions.  Data ownership and licensing related risks may not be currently addressed in existing contract and legal reviews and M&A due diligence activities including:

  • Training Data: AI systems heavily rely on training data - which is often scraped or open-source data where ownership and data usage rights are not clear. Understanding and documenting training data flows is the first step.

  • Data Quality: AI data pollution occurs when the data used to train or operate AI models is flawed, incomplete, or biased, potentially leading to biased predictions, unreliable recommendations, and inaccurate insights

  • Clarity of Ownership: Determining ownership of training data can be complex and uncertain. It might be subject to claims by third parties, infringement claims, privacy issues or other legal restrictions. This uncertainty could impact not only the use of training data, but also ownership of algorithms built using that data and any synthetic data created.

  • Use Limitations: If training data has use limitations, it can restrict how a company commercializes and licenses the data, develops technology, and applies algorithms.

Data ownership and licensing can impact the value of a transaction and limit the utility of acquired technology and data, and companies should update their contract review and M&A due diligence processes accordingly.

Request more information on DelCreo’s Risk Universe and risk assessment services.

As a reminder, here are our Risk Universe categories that we leverage to tackle and understand risk which include:

  • External Risk

  • Governance Risk

  • Strategic Risk

  • Product Risk

  • Business Operations Risk

  • Legal & Compliance Risk

  • Financial Risk

  • Technology Risk

These high-level risks are fairly consistent between different companies and risk profiles.

We leverage our understanding of risk maps and risk universes to better advise our clients in strategic business decisions and to optimize the management of risk throughout the enterprise.

Weighing the Risks

Weekly Highlights

  • AI Transparency and Risk Management: The lack of transparency in AI training and governance frameworks represents a significant risk as organizations increasingly rely on these technologies. This issue can lead to decreased user trust and potential conflicts, emphasizing the need for clearer transparency and robust governance models in AI deployment.

  • AI Impact on Utilities and Efficiency: AI technologies, particularly in natural language processing, are transforming the utilities industry by enhancing efficiency and sustainability. AI applications in this sector include anomaly detection in pipelines and customer service improvements, showcasing AI's role in driving operational improvements.

  • AI and Economic Implications: Advanced AI technologies are expected to automate significant portions of jobs in advanced economies, posing risks of mass job displacement. Despite the potential productivity benefits, this raises socioeconomic concerns that necessitate careful consideration and preparation by businesses and policymakers.

  • Recommendation for Business and Risk Managers: To effectively manage these AI-driven changes, business and risk managers should prioritize establishing comprehensive AI governance frameworks that address transparency, ethical considerations, and socioeconomic impacts. By doing so, they can mitigate risks and leverage AI's benefits responsibly, ensuring sustainable integration into their operational and strategic plans.

Risk Universe Weekly Updates

External Risk

  • Transparency is sorely lacking amid growing AI interest

    • Transparency issues surrounding the training of foundation models and the lack of clear governance frameworks pose significant external risks as organizations increasingly adopt AI, potentially leading to tension with users and impacting trust in AI systems.

    • Despite the growing investment in AI technologies in the Asia-Pacific region, concerns persist regarding transparency, with only a fraction of AI expenditure directed towards generative AI, highlighting the need for broader approaches to AI deployment that prioritize accessibility, flexibility, and transparency to address industry and demographic change risk factors.

  • How AI Is Shaping The World Of Utilities

    • The expansion of AI models and natural language processing in the utilities industry is driving significant demand for power, with experts showcasing various AI applications at the SAP for Energy and Utilities Conference.

    • AI is being utilized in diverse ways across the utilities sector, from detecting anomalies in pipelines and optimizing hydrogen infrastructure to improving customer experience and enhancing asset management, highlighting the critical role of AI in enhancing efficiency and sustainability within the industry.

  • An Inflation Test Looms Over the Economy and the Election

    • Economic analysts are closely monitoring inflation data this week amid divergent opinions on whether the Fed will cut interest rates by Election Day, with implications for the ongoing debate over President Biden's economic policies.

    • Key economic indicators, including the Consumer Price Index report, are expected to provide insights into inflation trends, influencing the Fed's decision-making on interest rates and shaping market expectations for monetary policy adjustments.

  • Why a debt-fueled US economy is facing a hard landing in 2025, chief economist says

    • Economist Torsten Slok predicts that while the US economy will maintain stability in the near term, growth drivers could transition into obstacles by next year due to high debt levels among consumers and corporations, potentially leading to a hard landing in 2025.

    • Rising delinquencies in credit cards and auto loans, coupled with concerns about highly-leveraged firms across various industries, indicate underlying economic vulnerabilities despite current low unemployment rates, raising concerns about the potential fallout when economic conditions worsen.

Governance Risk

  • Advanced AI tools may become a “massive issue” for jobs, says OpenAI CEO Sam Altman

    • OpenAI CEO Sam Altman expressed concerns about the socioeconomic impacts of advanced AI tools, particularly regarding mass job replacement and its potential effects on the economy, highlighting the need for serious consideration of these issues.

    • Studies suggest that advanced AI technologies could automate nearly half of the jobs in advanced economies, posing a significant risk of mass job replacement, prompting CEOs to acknowledge the potential for AI to both enhance productivity and efficiency while also replacing certain roles entirely.

  • In the rush to adopt AI, ethics and responsibility are taking a backseat at many companies

    • The rapid deployment of generative AI technology in workplaces, driven by executives' enthusiasm for its productivity benefits, is seen as necessary for maintaining competitiveness, according to a report by Microsoft and LinkedIn.

    • Despite the perceived benefits, adopting AI technology also brings risks, including reputational, financial, and legal harm, which companies struggle to identify and address due to the lack of adequate risk management capabilities and expertise, compounded by a disproportionate focus on innovation over governance in investment and regulatory efforts.

Strategic Risk

  • Tech investments often driven by fear of missing out

    • Many CIOs feel pressured to invest in emerging technologies to stay competitive, with AI being perceived as particularly risky due to both its potential and the moral imperative to succeed, yet there's a high rate of failure compared to established technologies.

    • Despite substantial investments in emerging technology projects, predicting the return on investment remains challenging for most organizations, leading to cautious attitudes towards future investments and a focus on long-term rather than immediate ROI.

Financial Risk

  • M&A Transactions: Drafting AI Representations and Warranties for Non-AI Companies

    • The increasing use of artificial intelligence (AI) in various industries presents financial risks for businesses engaging in M&A transactions, including risks related to infringement, confidentiality, IP ownership, regulatory compliance, and indemnity obligations, which need to be identified, assessed, and properly addressed through due diligence and comprehensive terms in acquisition agreements.

    • Buyers should conduct thorough diligence to confirm rights and ownership related to AI technology, training data, and output, and may need to include custom representations and warranties in the acquisition agreement to cover aspects such as infringement, ownership of AI technology and output, licenses to inputs, and copyright and patent protections, tailored to the specific AI tools and purposes used by the target company.

Technology Risk

  • Don’t overlook the impact of AI on data management

    • Despite advancements in data management technologies like data warehouses, big data, and data lakes, many organizations still struggle with manual data entry, disconnected data across departments, and poor data quality, hindering their ability to access valuable insights.

    • Investing in AI-driven solutions for data collection and management, such as automated data capture and generative AI chatbots, can significantly improve data accuracy, streamline processes, and unlock new revenue opportunities through enhanced customer engagement and predictive analytics.

  • Does AI increase cloud computing risks?

    • Banks' increasing reliance on cloud providers like Google, Microsoft, and Amazon for both software applications and large language models raises concerns about concentration risk, potential outages, cybersecurity vulnerabilities, and lack of bargaining power in negotiations, which may lead to disruptions in operations and data privacy breaches.

    • The consolidation of power in AI models, especially those provided by a few major companies like OpenAI and those affiliated with hyperscale cloud providers, poses additional risks such as errors, biases, and lack of control, prompting calls for increased regulation and the exploration of alternative solutions through open-source communities.

  • German Companies Bet on AI But Payoff Could Be Years Away

    • German businesses are increasingly embracing artificial intelligence (AI) to enhance productivity, with applications ranging from automating processes to optimizing supply chains, although concerns such as data protection, workforce skills, and lack of use cases are hindering broader adoption.

    • While some companies like Henkel and Delivery Hero are actively leveraging AI technologies for automation and efficiency, Germany still lags behind other countries in AI enterprise adoption and investment in AI startups, suggesting that AI's transformative potential may not be fully realized in the near term.

  • The IMF's chief is sounding the alarm, says the AI revolution is striking the job market 'like a tsunami'

    • IMF Managing Director Kristalina Georgieva warns of AI's potential negative impact on the global job market, emphasizing the urgency for businesses and individuals to prepare for significant changes in employment due to AI integration.

    • Despite warnings from experts like Georgieva and OpenAI CEO Sam Altman about AI's potential to disrupt the job market, some believe that AI's rise will create new opportunities, particularly emphasizing the growing importance of soft skills alongside technical skills.