Business
Contracts to manage AI risk – The Royal Gazette

The BMA’s 2025 Business Plan signalled future policies concerning the risk-managed use of AI by its registrants
This is the first of a two-part article on how artificial intelligence contracts can be used to manage the development and use risks associated with such transformative technology.
All transformational technology is fraught with risk. However, when it comes to AI, Elon Musk said “we are communing with the devil”.
As a commercial lawyer, I like to think that fables about contracts with the devil exist because contracts are the ultimate risk management tool.
Regulators around the world, including the Bermuda Monetary Authority, fully appreciate the importance of using contracts to mitigate, if not avoid, the risks associated with the development and use of transformative technologies.
The BMA’s 2025 Business Plan signalled future policies concerning the risk-managed use of AI by its registrants.
That plan stated that the BMA was “undertaking a review of the Insurance Code of Conduct and the Operational Cybersecurity Code of Conduct to consider the merits of integrating specific guidelines on the use of AI and machine-learning systems”.
As with the BMA’s regulatory requirements for outsourcing and cybersecurity governance, I fully expect that the evolution of those current regulations will include additional risk management guidance involving AI contracts that are relied upon by Bermuda’s financial service sector.
In that regard, the recent emergence of model contracts for all sectors to manage the many risks of AI has been striking.
Among the variations of AI model contracts that I have consulted, there are two that stand out.
In 2023, Britain’s Society for Computers and Law published a 59-page White Paper titled Artificial Intelligence Contractual Clauses, and recently the Digital Transformation Agency of the Australian Government published [AI] Model Clauses, Version 2.0. Both are excellent.
Both organisations take a pragmatic approach to crafting contractual provisions that specifically address the commercial and legal risks of AI development, commercialisation and use. There is nothing abstractly academic about that guidance.
The commercial risks associated with all transformative technology, including AI, include the risks that:
• The technology doesn’t perform the way that the vendor promised it would
• Due diligence is difficult to undertake on products and vendors that are new to the market
• The solution’s operation may not be compatible, interoperable or easily integrated with legacy systems
• The solution’s performance reliability is yet to be proven
To address those “new-to-market” risks, both the SCL and DTA recommend that AI contracts include terms that:
• Define the operational and functional specifications of the solution in precise and empirically verifiable terms
• Require either a vendor-led AI demonstration or an operational demonstration within the customer’s infrastructure
• Require acceptance testing as a precondition to contract effectiveness and any licence fee payments
• Stipulate a warranty (of reasonable duration) concerning the solution’s “on spec” operation and that requires expedited defect remediation
Where AI is offered as a service rather than as licensed software, the contract should also address the usual risks that are associated with:
• The different variations of cloud or distributive computing
• Any jurisdictional export control restrictions
• Compliance with all privacy laws, including export restrictions
• The service provider’s compliance with all applicable law, including outsourcing and cybersecurity regulations
• Subcontracting restrictions
• A prohibition on the re-export of data to other jurisdictions
Since many AI solutions are powerful search agents that function as scrapers and “crawler bots”, two of the most prominent and serious AI risks to contractually address are the misappropriation of personal (and often confidential) information that the AI solution accesses, views and copies or uses, and the unlicensed reprography and misappropriation of third-party intellectual property.
As intelligent as AI may appear, it may be unable to identify data and content that is the property of others.
Based on the AI copyright infringement cases that are now before the courts in the US and Britain, AI contracts should include broadly drafted third-party non-infringement covenants as well as indemnities to protect users from such third-party liability. That approach to manage the risk of intellectual property infringement is required for all content or data that AI finds, fetches and brings back to the doorstep.
More specifically, the SCL and DTA suggest that AI contracts include covenants to:
• Ensure that the AI provides only original work
• Ensure that AI does not merely customise, enhance or create derivative works of someone else’s property
• Address whether the service vendor owns the AI or the AI otherwise relies on “open source” software
• Provide that neither the use nor operation of the AI will breach any third-party rights, including any contractual, privacy, intellectual property or statutory rights
Next week, in part two, I will identify additional development and use risks that AI brings, and the contractual terms that are necessary to address those risks.
• Duncan Card is a partner at Appleby who specialises in information technology and outsourcing contracts, privacy law and cybersecurity compliance in Bermuda. A copy of this column can be obtained on the Appleby website atwww.applebyglobal.com. This column should not be used as a substitute for professional legal advice. Before proceeding with any matters discussed here, consult a lawyer
Business
Fresh News: WebHopers Digital Marketing Company in India Unveils the AI-Driven Campaigns by Google Search & LLMs

In today’s fast-paced world, Digital marketing without AI is like fishing in an empty pond – Lots of effort but few results. From finding a shop to buy a product or anything else, nearly every customer begins their search with an AI-powered platform, shaping the decisions in real time. WebHopers exploits the AI to transform the marketing strategies, consumer behaviour, and analyzes the data to ensure the campaigns are Focused, Custom-made, and strongly influential on users. The reason behind this is AI, where things get interesting. It can analyze data, consumer behaviour in real time and predict what people want. Even businesses are not asking now that they should use AI or not, but the real question is how often they can make it a part of their marketing strategies. AI insights allow brands to create a user-friendly and engaging experience like never before.
From Insights to Results: The Growing Demand for AI in Marketing AI is not just limited to data analysis but also covers a wide area of consumer insights that fuel the unstoppable demand across industries.
• The Artificial Intelligence in marketing has a market size of USD 12.7 billion in 2024 as per Cognitive Market Research.
• As per SEMrush, ChatGPT comes in 5th rank on top websites on a global level, and it has 5.38billion visits in August 2025.
• Artificial Intelligence reduces the 20% time to launch the campaign and increases the personalized audience segment by 30% as per Semrush.
Decoding the Power of AI-Driven Campaigns AI-Driven Campaign is the next-generation strategy to reach the right audience online. This is different from Traditional campaigns in which marketers guess the users and target a broad segment. AI-driven campaigns show the right ad to the specific audience at the right time.
Consider this scenario: An Online marketplace brand that sells home decor and furniture items. In the past, they had to guess what the customer wanted and hoped for, but after the AI integration, it completely changed the way of plan ad campaigns. It can now analyze the real-time customer data and top queries such as “Study chairs for small apartments” or “Slider wardrobe under 6000”, and many more. Once AI tells the user’s needs, LLMs like tools can create an exactly fitted ad that users are looking for.
AI Meets Google Search: Redefining Ad Campaigns with LLMs The best marketing does not feel like marketing until businesses do not show to specific and targeted audiences. For this, it is important to know what people are searching for. Google searches provide the insights for what users are searching for, and Large Language Models convert insights into highly personalized and attractive ad campaigns. Let’s see how Google search & LLMs are used for Ad Campaigns: Keyword Targeting with Google Search Keywords are the main foundation for Google Ad Campaigns. Marketing companies search for words or phrases through Keyword planner tools, such as Google Keyword Planner, that show what their target audience is searching for.
Creating Relevant Ads with LLMs After choosing the related keywords, marketers design an ad copy and visuals by LLM tools that match with keywords and the user’s intent. Clear, engaging and relevant to queries, ads are more likely to reach the right audience.
Targeting a Specific Audience Google Ads allows businesses to create a filter for their ads according to: • Location • Device • Demographics • Time By combining LLMs with Google search, right Ads reach the right audience at the right time, which increases the chance of engagement and conversions.
Search Intent for Custom Strategies Google search and LLM provide the search intent and patterns from real-time data. With that business can strategically run campaign aids. Let’s understand this with an example: Users searching for “Family-friendly resort in Manali” can see an ad related to kid-friendly activities in Manali, “special family packages for Manali,” and many more.
Tracking Performance and Optimizing Campaigns Google search ads also allow marketers to analyze the results by tracking the advertising. It shows: • Click Through Rates • Conversions & Sales • Highly driven Keywords • User behaviour with the ad The Business Advantage of AI-Driven Campaigns AI-driven marketing has changed the way of digital marketing. Now, the small to large business models rely on Human Expertise and AI. This combination truly made the customer experience more engaging for the ad campaigns. Adding real-time data and search queries by AI, while humans add emotions and personalization to it, makes the ad campaigns more beneficial for the business. Here are some of the benefits of using AI for ad campaigns: • Precision Targeting • Personalized Customer Experience • Increase Efficiency and Scalability • Real Time Optimization • Better ROI • Competitive Advantage Future Trends: AI, Google Search, and LLMs in Digital Marketing Digital Marketing is in unstoppable growth, and a Combination of AI, Google Search and LLMs is the new era of innovation. Those businesses that adopt these technologies are likely to gain a high percentage of users. Future trends are evolving digital marketing such as: • Hyper-personalised marketing • Predictive Marketing • Voice & Visual Search Integration • Automation at Scale • Smarter Ad Optimization Final Thought AI-driven campaigns powered by Google Search and LLMs are not just an option but have become the future of personalized and effective digital marketing. By leveraging these technologies, businesses can easily reach their valuable customers. Behind all this process, a trusted and experienced marketing company plays a crucial role, and this is where WebHopers AI-Powered Digital Marketing company in India stands out to deliver the AI-Driven Campaigns with Google Search & LLM Models.
Contact Details Name – WebHopers Infotech PVT LTD Email – info@webhopers.com Phone Number – 9056855559 (Disclaimer: The above press release comes to you under an arrangement with NRDPL and PTI takes no editorial responsibility for the same.). PTI PWR
(This content is sourced from a syndicated feed and is published as received. The Tribune assumes no responsibility or liability for its accuracy, completeness, or content.)
Business
Dan Ives Says Tesla’s AI And Robotaxi Business Worth At Least $1 Trillion, Company And Musk Headed For ‘Important Chapter’ In Growth Story – Tesla (NASDAQ:TSLA)

Over the weekend, Wedbush Securities analyst Dan Ives said Tesla Inc. TSLA is on the verge of its most significant phase yet, arguing that the company’s artificial intelligence and robotaxi ambitions could unlock at least $1 trillion in value.
AI Revolution And Robotaxi Potential
“We believe Tesla and Musk are heading into a very important chapter of their growth story as the AI revolution takes hold and the robotaxi opportunity is now a reality on the doorstep,” Ives wrote on X, formerly Twitter. “We estimate the AI and autonomous opportunity is worth at least $1 trillion alone for Tesla.”
Ives’ remarks followed a Wall Street Journal report that Stephen Hawk, a 56-year-old Tesla investor from Florida, had filed a shareholder proposal urging Tesla’s board to approve an investment in xAI.
Following the report, SkyBridge Capital founder Anthony Scaramucci also said that a Tesla–xAI merger “feels inevitable.”
Delivery Momentum Fuels Near-Term Gains
Earlier this month, Gary Black, managing partner at The Future Fund LLC, said Tesla’s stock surge in the past few days stems from expectations that the company will exceed Wall Street’s third-quarter delivery forecasts.
“Let’s not kid ourselves,” Black wrote on X. “$TSLA has been strong the past few days NOT because of progress on robotaxi but because every hedge fund has come to the realization that $TSLA will crush 3Q delivery estimates in two weeks.”
Black estimates Tesla will deliver 470,000 vehicles in the quarter, well above Wall Street’s consensus of 432,000, aided by buyers rushing to take advantage of the expiring $7,500 EV tax credit on Sept. 30.
What Are The Mixed Global Signals
Tesla’s performance remains uneven across markets. In China, sales fell 10% in August, marking the sixth monthly decline in 2025. Still, early September saw a rebound, with registrations hitting 14,300, a 41% jump from the previous quarter’s weekly average.
In the U.S., rising vehicle prices have weighed on Tesla’s market share even as overall EV sales climb.
Skepticism On Autonomy And Leadership
Not all observers are convinced Tesla can deliver on Ives’ trillion-dollar thesis.
Ross Gerber, co-founder of Gerber Kawasaki, earlier questioned Tesla’s approach to autonomy, saying Musk has ignored hardware issues critical to self-driving safety.
An ex-employee also criticized Musk’s leadership as “seriously compromised,” alleging it had damaged Tesla’s mission.
Tesla Stock Lags Behind S&P 500 And Nasdaq 100
In July, Tesla reported second-quarter revenue of $22.5 billion, down 12% year-over-year and short of analyst estimates.
At the time, the company reiterated plans to launch a more affordable model later in 2025 while preparing the Tesla Semi and Cybercab for volume production in 2026.
On the analyst front, Tesla carries a consensus price target of $311.81 based on 29 ratings. The three latest updates include Wedbush, RBC Capital and China Renaissance, with their average target of $391.33 suggesting a slight 1.07% downside.
Price Action: So far in 2025, Tesla’s stock is down about 2%, underperforming the S&P 500’s 11.95% gain and the Nasdaq 100’s 14.66% increase, according to Benzinga Pro.
Benzinga’s Edge Stock Rankings indicate that TSLA continues to show strength across short, medium and long-term horizons, with additional insights available for investors.
Read Next:
Photo Courtesy: Josiah True on Shutterstock.com
Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors.
Business
How North Korean and Chinese Hackers Infiltrate Companies With AI

From bogus IDs to made-up résumés, North Korean and Chinese hackers have been using AI tools to supercharge espionage and slip into companies and other targets.
In the latest case, a North Korean hacking group known as Kimusky used ChatGPT to generate a fake draft of a South Korean military ID. The fake IDs were attached to phishing emails that impersonated a South Korean defense institution responsible for issuing credentials to military-affiliated officials, South Korean cybersecurity firm Genians said in a blog post published Monday.
Kimsuky has been linked to a string of espionage campaigns against individuals and organizations in South Korea, Japan, and the US. In 2020, the US Department of Homeland Security said the group is “most likely tasked by the North Korean regime with a global intelligence-gathering mission.”
ChatGPT blocks attempts to generate official government IDs. But the model could be coaxed into producing convincing mock-ups if the prompt was framed as a “sample design for legitimate purposes rather than reproducing an actual military ID,” Genians said.
This is not the first time North Korean hackers have used AI to infiltrate foreign entities. Anthropic said in a report last month that North Korean hackers used its Claude tool to secure and maintain fraudulent remote employment at American Fortune 500 tech companies. The hackers used Claude to spin up convincing résumés and portfolios, pass coding tests, and even complete real technical assignments once they were on the job.
US officials said last year that North Korea was placing people in remote positions in US firms using false or stolen identities as part of a mass extortion scheme.
China’s hackers are doing it, too
Anthropic said in the same report that a Chinese actor spent over nine months using Claude as a full-stack cyberattack assistant to target major Vietnamese telecommunications providers, agricultural systems, and government databases.
The hacker used Claude as a “technical advisor, code developer, security analyst, and operational consultant throughout their campaign,” Anthropic said.
Anthropic said it had implemented new ways to detect misuse of its tools.
Chinese hackers have also been turning to ChatGPT for help with their cyber campaigns, according to an OpenAI report published in June. The hackers asked the chatbot to generate code for “password bruteforcing”— scripts that guess thousands of username and password combinations until one works. They used ChatGPT to dig up information on US defense networks, satellite systems, and government ID verification cards.
The OpenAI report flagged a China-based influence operation that used ChatGPT to generate social media posts designed to stoke division in US politics, including fake profile images to make the accounts look like real people.
“Every operation we disrupt gives us a better understanding of how threat actors are trying to abuse our models, and enables us to refine our defenses,” OpenAI said in the June report.
It’s not just Claude and ChatGPT. North Korean and Chinese hackers have experimented with Google’s Gemini to expand their operations. Chinese groups used the chatbot to troubleshoot code and obtain “deeper access to target networks,” while North Korean actors used Gemini to draft fake cover letters and scout IT job postings, Google said in a January report.
Google said Gemini’s safeguards prevented hackers from using it for more sophisticated attacks, such as accessing information to manipulate Google’s own products.
OpenAI, Anthropic, and Google did not respond to a request for comment from Business Insider. The companies have said they published their findings on hackers to help others improve security.
AI makes hacking easier
Cybersecurity experts have long warned that AI has the capacity to make hacking and disinformation operations easier.
Hackers have been using AI models to infiltrate companies, Yuval Fernbach, the chief technology officer of machine learning operations at software supply chain company JFrog, told Business Insider in a report published in April.
“We are seeing many, many attacks,” Fernbach said, adding that malicious code is easily hidden inside open-source large language models. Hackers typically shut things down, steal information, or change the output of a website or tool.
Online businesses have also been hit by deepfakes and scams. Rob Duncan, the VP of strategy at the cybersecurity firm Netcraft, told Business Insider in a June report that he isn’t surprised at the surge in personalized phishing attacks against small businesses.
GenAI tools now allow even a novice lone wolf with little technical know-how to clone a brand’s image and write flawless, convincing scam messages within minutes, Duncan said. With cheap tools, “attackers can more easily spoof employees, fool customers, or impersonate partners across multiple channels,” he added.
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