AI Legal Risks, Return Fraud, and Tech Innovations in 2026
At our AI Smart Labs session on June 18, we mapped out a new PR outreach process to handle outbound podcast and interview queries. Our team decided to drop our process directly into a workflow and SOP creator to generate clear instructions for the team. ou can automate tedious relationship-building tasks, and you still need human oversight to verify the output before sending a pitch.
The AI you are building on is not yours to fully control, which makes setting up these standard operating procedures critical. If you do not understand the tools your team and your customers are using, you are taking on hidden risks. You need clear policies and an understanding of where your data goes.
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Here are the top stories from this week…
How to Handle AI Discount Demands
Giving in to discount demands will destroy your margins. Clients often assume that because you use AI, your work takes less time and should cost less. We break down the exact scripts and pricing models you can use to protect your revenue while still delivering value.
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Shoppers Are Using AI to Exploit Return Policies
Nearly half of online shoppers are using AI tools to write fake complaint emails and secure refunds without returning the actual items. E-commerce platforms are struggling because standard customer service software cannot easily tell the difference between a real frustrated buyer and an AI script.
My Take: If you sell products online, your standard operating procedures are suddenly a vulnerability. We see clients relying on old customer service rules that AI easily bypasses. AI is not just a tool for your team; your customers are actively using it against you. It is time to update your policies, and you can use our free Workflow & SOP Creator to tighten up your operations. Where are you vulnerable?
Source: Business Wire
German Court Holds Google Liable for AI Answers
A German court ruled that Google is legally responsible for incorrect answers generated by its AI search overviews. Two publishing companies sued because Google’s AI falsely connected them to fraudulent schemes, and the court decided that standard disclaimers cautioning users to verify information do not protect the tech giant.
My Take: This is a major shift in liability. If courts decide AI platforms are responsible for the content they generate, the wild west of AI answers will close quickly. In plain terms, you cannot just blame the algorithm when something goes wrong. Be extremely careful when deploying AI chatbots for customer service. You are responsible for what your AI says to your customers.
Source: ASIS Online
White House Executive Order Targets AI Cybersecurity
A new executive order directs federal agencies to strengthen their cyber defenses and prioritize prosecuting criminals who use AI for cyberattacks. It also sets up a voluntary system for developers to let the government test advanced AI models before they are released to the public.
My Take: Regulation is moving toward security over innovation. While the testing is voluntary right now, the focus on criminal enforcement shows the government is getting serious about AI threats. If you do not have clear security protocols for how your team uses AI, you are taking unnecessary risks. Lock down your data first. Do you even know what the data policies are for the tools your team uses daily?
Source: Holland & Knight
MIT Researchers Speed Up Metal Manufacturing
Scientists at MIT have developed a new AI model that predicts how metal alloys will behave under stress. This cuts down the physical testing time required to develop new materials for manufacturing and construction.
My Take: Industrial intelligence is moving quickly from software labs to physical factories. Faster material evaluation means quicker product testing cycles and lower overhead costs for industrial vendors. Watch this shift closely to negotiate better pricing with your supply chain partners.
Source: MIT News
AI Tool Reveals Hidden Organ Damage
Researchers at Oxford developed an AI tool that predicts how high blood pressure damages different organs before major problems occur. By combining hundreds of data points, including scans and blood tests, the AI can find patterns that simple blood pressure readings miss.
My Take: AI is completely changing preventative medicine. Instead of waiting for a heart attack to show the damage, doctors can now see the exact path a patient is on. This level of predictive data will soon be the standard across all healthcare. It is a perfect example of how combining existing data with machine learning saves lives.
Source: UK Research and Innovation
Tool picks of the week
- Workflow & SOP Creator – Maps your business operations, builds clear charts, and integrates automation to remove manual bottlenecks. We use this constantly to document our own internal workflows and SOPs so our team knows exactly how to handle any situation.
- Gamma – AI tool for creating presentations, documents, and websites quickly. My personal favorite, 3 years running!
- OS CRM – Automated CRM for client management, pipeline, LMS, and so much more. It’s built on GHL and integrates easily with AI tools.
Join the Conversation
Got a burning question, a fresh take, or just want to share your latest AI wins? Hit us up at [email protected]. Your insights keep this community growing and thriving!
Have a great day!
-Nicole A. Donnelly
Founder, AI Smart Ventures
AI Strategy – AI Training – AIConsulting – AI Implementation
