Escrow's slipping. The lender's dragging. An inspection response is 48 hours late. Most agents grab the Additional Clause Addendum or a Contract Amendment and try to negotiate their way out of it. Both are the wrong form. The correct instrument is the Cure Period Notice; three-day clock, formal breach, contract-terminating teeth. Here's how it actually works, and why the alternatives leave earnest money on the table.

Artificial intelligence is quickly becoming the front door to the homebuying journey. According to a recent National Association of REALTORS® article, buyers—particularly Millennials and Gen Z—are increasingly using AI tools to estimate affordability, understand mortgage payments, research neighborhoods, and make sense of the overall purchasing process. Yet the takeaway is not that AI is replacing agents; it is raising the bar for how real estate professionals show up online.

Every designated broker we've talked to says the job has gotten harder. The NAR settlement changed the paperwork. AAR forms keep drifting. The class-action climate raised the stakes. And A.R.S. § 32-2151.01 puts the burden of policy, training, and record-keeping squarely on the DB. Adding a chatbot doesn't solve it. Here's what does.

A Fyxer report found 90% of real estate professionals use AI, but only 35% consider it genuinely helpful. Researchers say reliance on generic tools, limited workflow integration and underused email automation are hindering productivity, while industry-specific, integrated AI platforms offer the greatest potential for meaningful efficiency gains.

Most AI tools sold to real estate right now are summary machines: they rewrite listings, tighten emails, and transcribe voicemails. Useful on the edges, but not transformative — because summarization is where the real work starts, not where it ends. The version of AI that changes the daily broker workflow reads the compliance corpus and acts on it. Here's what that looks like, and why it matters for supervisory brokers.

The most avoidable dispute in an Arizona residential resale happens 24 hours before close: the buyer walks the property and the chandelier is gone. Line 39 of the RRPC is explicit about what conveys with the sale — most agents just haven't read it closely enough to spot the issue at the offer stage.

Every listing agent in Arizona has heard some version of this question from a buyer's agent: "My client wants to sweeten the offer with non-refundable earnest money. How do we do it?"Most agents guess. Some call their broker. A few make up custom language and hope escrow doesn't push back.None of that is necessary. The Arizona Association of Realtors already wrote the clause.

Why does AI seem to devour computing power? Data centers are popping up everywhere, putting pressure on the power grid and raising environmental concerns, all because modern AI systems consume a remarkable amount of energy to run effectively.

AI is fueling high demand for compute power, spurring companies to invest billions of dollars in infrastructure. But with future demand uncertain, investors will need to make calculated decisions.

Artificial Intelligence is transforming how we live and work. From helping us find information on the internet to driving our cars, AI is becoming an integral part of our daily lives. But when it comes to serious matters like legal and financial questions, can we really trust AI to provide the right answers?

Even as language models become more capable, one challenge remains stubbornly hard to fully solve: hallucinations. By this we mean instances where a model confidently generates an answer that isn’t true.

Over the last eight years, since the first tokenized real estate deals were completed, tokenization has helped open potential new avenues for real estate investment through fractional ownership.

In the exciting world of artificial intelligence (AI), one of the most important concepts to understand is "training data." But what does this term really mean? Why is it so crucial for AI? In this article, let’s break it down into simple terms that everyone can understand, whether you’re well versed or someone with no experience in AI.

AI can speed up work but cannot match human empathy or nuanced thinking. The 30% Rule keeps humans as key decision-makers while AI handles routine tasks. This approach safeguards jobs by blending automation with human strengths. It creates a balanced system where technology and people work together.

Practical insights about generative AI, brokerage enablement, and the leadership philosophy behind RETEQ’s offerings.

New tools and resources to support families, and notifications to keep teens safe.

In the world of artificial intelligence (AI), we often hear impressive stories about how machines can learn from data and make decisions. Whether it's recommending your next favorite movie or helping doctors diagnose illnesses, AI holds incredible potential. However, one intriguing aspect of AI is its unpredictability. You might ask, "Why can't we always get the same result from an AI?" This question leads us to explore the fascinating world of AI algorithms, data, and randomness.

Some conclusions are, specifically that ChatGPT – used by 700 million people weekly by the end of July – is being engaged more for personal tasks, including writing and research, while Claude is being leaned on for work-related jobs.

OpenAI has announced it is developing an AI-centered jobs platform as part of broader efforts to expand AI literacy, and as the company grows its consumer and business-facing AI applications.

The ChatGPT maker’s “OpenAI Jobs Platform” will utilize AI to help connect qualified job candidates to companies, which could put it in competition with Microsoft’s LinkedIn. 

OpenAI said Tuesday it plans to route sensitive conversations to reasoning models like GPT-5 and roll out parental controls within the next month — part of an ongoing response to recent safety incidents involving ChatGPT failing to detect mental distress.