What The Draft Order Would Have Done 

The plan proposed to block any state-level AI laws, instead allowing the federal government to create a uniform national standard. Under it, states with their own AI laws could face legal challenges or loss of federal funding. 

David Sacks As AI Policy Gatekeeper 

The order would have made Sacks, currently a special adviser for AI and crypto, the central figure overseeing enforcement: all key decisions from lawsuits to funding withdrawals would pass through his office. 

Pushback From Both Sides Of The Aisle

Surprisingly, support for state-level AI regulation came from a mix of progressive Democrats and hard-right Republicans, united by distrust of Big Tech and concern over the concentration of power. 

Legal And Political Infeasibility Exposed

Many legal experts predicted that the order’s sweeping powers, especially preempting states and reallocating federal funds, would be hard to defend in court; internally, the administration acknowledged these concerns. 

The Order Was Shelved 

Amid the storm of controversy, the executive order was never signed. Instead, a more modest, uncontroversial AI-related order was issued, one focusing on AI research in national labs, not on overriding state laws.

Lawsuit Resolved through Partnership 

Warner Music Group has settled its copyright infringement lawsuit against AI music platform Suno by signing a licensing agreement. 

Artist Control is Central 

The deal gives artists and songwriters full control (opt-in) over whether their names, voices, likenesses, and compositions are used in AI-generated music. 

New Licensed AI Models Coming in 2026

Suno will retire its current models and launch more advanced, licensed ones in 2026. 

Download Restrictions Imposed

Under the new terms, users will need a paid account to download audio. Free-tier users can play and share AI songs, but not download them; paid users face monthly download limits. 

Acquisition of Live-Music Platform 

As part of the agreement, Suno acquires Songkick (a concert-discovery platform) from Warner, aiming to deepen fan-artist connections via live events and AI creation. 

Clarify Your Marketing Objectives & Audience Insights

Start by defining what you want the campaign to achieve: brand awareness, lead generation, sales growth, or engagement. Provide AI with details about your target audience, including demographics, interests, pain points, and buying behavior. 

Feed AI Your Brand Identity & Messaging Inputs

Share your brand voice, value proposition, past campaign examples, product benefits, and unique selling points. The more context you provide, the more tailored and on-brand your AI-generated ideas will be.  

Ask AI to Generate Multi-Channel Campaign Concepts

Give the AI a clear prompt to create campaign ideas for platforms like social media, email, paid ads, landing pages, and video content. AI can brainstorm themes, angles, hooks, and storytelling formats, giving you a range of creative concepts within seconds.

Refine & Expand the Best Ideas with AI Iterations

Choose your top campaign ideas and ask the AI to expand them. You can request variations in tone, rewrite for different audiences, generate multiple ad versions, or transform a concept into scripts, captions, or taglines.  

Convert Campaign Concepts into Ready-to-Use Assets

Use AI to turn approved concepts into real marketing materials, social media posts, email copy, ad creatives, short-form video scripts, and content calendars. Many AI tools also create design assets or provide templates, helping you go from concept to deployment quickly.

Airgram

Airgram is an AI-powered meeting assistant that automates the tedious parts of meetings, recording, transcribing, and summarizing conversations, so teams don’t have to rely on manual note-taking. It supports live transcription, creates searchable text versions of calls, and automatically extracts key insights and action items after the meeting. It integrates with major videoconferencing tools (like Zoom, Google Meet, Microsoft Teams), and lets users share meeting snippets, assign tasks, and collaborate on notes. 

Verint Customer Engagement

Verint Customer Engagement is an enterprise-grade AI and analytics platform designed to improve customer experience (CX) across contact centers, chat, and digital channels. It leverages AI, including speech analytics, intent recognition, and sentiment analysis, to monitor and analyze customer interactions at scale. The platform transforms unstructured communication data into actionable insights, enabling businesses to optimize contact-center workflows, improve service quality, detect problems early, and deliver better customer and employee experiences.

Semantix

Semantix is a full-suite AI & data-infrastructure platform that offers big-data analytics, data governance, ML, generative AI, and advanced data-processing tools, aimed at helping enterprises turn complex data into strategic decisions. Its modules include a Data Analytics Hub for processing large datasets, an ML Hub/GenAI Hub for building and deploying AI solutions, and tools for integration, data visualization, and governance. Semantix is used across industries like finance, healthcare, retail, and pharma to build custom AI/data workflows without heavy infrastructure overhead.

Syte

Syte is an AI-powered visual product discovery and recommendation platform built for e-commerce, especially fashion, apparel, and retail. Using visual-AI enables features like image-based visual search, “shop the look/room,” similarity-based recommendations, and AI-driven tagging and merchandising. The platform helps customers find products they love through intuitive, image-driven workflows, making shopping more natural and visual, not just keyword-based. 

Atlast

Atlast is an AI-powered platform (stealth-stage) that aims to provide intelligent workflow automation for enterprises. While specific product details are limited, the startup appears focused on using AI to optimize business processes, improve operational efficiency, and reduce manual overhead. Its early-stage positioning suggests that it is building core technology and preparing for wider market adoption.

Dayli

Dayli is an early-stage AI startup (stealth mode) with limited public information available. It appears to be exploring applications in AI-powered productivity or analytics tools, though the exact focus and product offerings are not yet publicly disclosed. Its small team and early-stage development suggest it is still in product validation and technology-building phases.

Circle Flake

Circle Flake is a stealth AI startup with minimal public footprint. Based on early-stage job postings and Wellfound listings, the company is likely exploring AI applications in software, automation, or analytics. With little available data, it is positioned as an emerging player building foundational technology for future deployment.

LendingIQ

LendingIQ is an AI-powered fintech startup focused on automating loan underwriting and credit-risk evaluation. The platform uses machine learning to accelerate decision-making, improve accuracy, and increase inclusivity for borrowers who lack traditional credit histories. By streamlining underwriting workflows, LendingIQ helps financial institutions reduce operational overhead and scale lending while maintaining compliance with regulatory standards.