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IN THIS ISSUE: A review of the book, “The Non-Obvious Guide to Using AI for Marketing” by David Berkowitz, a clear, practical resource for marketers trying to make sense of AI without getting lost in jargon or hype. Plus, why did Salesforce pay $8 billion for Informatica? Short answer: It’s the data.
The Prompt
Over a year ago, I spoke with David Berkowitz, founder of the AI Marketers Guild (AIMG), about how he’s helping marketers make sense of the fast-evolving AI landscape. At the time, he described generative AI as a kind of superpower for these professionals, a tool that could dramatically amplify their creativity and productivity. As a marketer, I was intrigued by his insights into the technology, so I was especially excited to see that he recently published a book on the topic.
Released in March, “The Non-Obvious Guide to Using AI for Marketing: How to Harness the Transformative Power of AI” is a handy guide for marketers of any level looking to jumpstart their AI journey. Spanning 175 pages, the book is free of technical jargon—there is a glossary at the end, if needed—but filled with actionable insights anyone can take to supplement their organization’s marketing initiatives. It doesn’t matter if you’re a freelancer, work in a small business, or are part of a corporate team; Berkowitz has written what might be the perennial introductory manual everyone should read before diving headfirst into AI.
There are 12 lessons covered in “The Non-Obvious Guide to Using AI for Marketing,” from assessing how prepared you are for AI and how to integrate the technology into your marketing strategy to identifying the right tools for the job, creating the optimal AI prompts, creating customer personas and personalization with AI, and measuring the success and ROI of AI-driven initiatives. But instead of lecturing readers about the technology, Berkowitz infuses each chapter with case studies and provides a summary of the key takeaways.
The result is a book that reads less like a textbook and more like a conversation with a trusted advisor, someone who has been experimenting, iterating, and learning alongside the rest of us. And Berkowitz truly has: AIMG isn’t just an online community group; it also functions as a consultancy, offering one-on-one interviews and workshops to companies. With this book, you’re essentially getting access to that same expertise, but at a fraction of the cost of a private consultation.
Will everything in “The Non-Obvious Guide to Using AI for Marketing” stand up to the test of time? It doesn’t appear so, as I’ve noticed at least one example already outdated. There’s a case study in Klarna’s embrace of AI for its customer service, only for the company to recently reverse course. Situations like this are hardly surprising, given the rapid pace of AI—what’s relevant today may be outdated in six months (or sooner). Unlike past technologies that remained stable for years, AI is evolving at breakneck speed. Case in point: One of the last sections in this book addresses AI agents, but in the two months since the book was published, the agentic era has experienced a surge in innovation.
Amid a flood of AI-related titles hitting the shelves, Berkowitz’s debut stands out for offering a fresh and practical perspective. It doesn’t dive deep into how a particular AI company was founded or approach it from a philosophical angle. Instead, “The Non-Obvious Guide to Using AI for Marketing” offers a tutorial on how marketers can make this technology their superpower.
Could the insights in this book apply beyond marketing? Absolutely. In many ways, everyone within an organization plays a role—directly or indirectly—in marketing. And at a time when so many professionals are anxious about job security, eager to stay ahead of the curve, and searching for meaningful ways to harness AI, Berkowitz offers a valuable resource. Rather than fueling fear, he encourages us to embrace AI thoughtfully and strategically.
He doesn’t promise magic if you follow his advice, but he does offer clarity. “The Non-Obvious Guide to Using AI for Marketing” meets you where you are and helps you move forward with confidence. If you want a practical, hype-free introduction to using AI in your marketing work, this book is worth your time.
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A Closer Look
Salesforce is on an AI acquisition spree. The enterprise tech company announced this week that it’s buying cloud data management firm Informatica for approximately $8 billion. This comes just days after Salesforce revealed its intention to acquire automation startup Convergence.io. Terms of that deal weren’t disclosed. Nevertheless, this is evidence that Chief Executive Marc Benioff is committed to being aggressive in helping companies adopt AI.
Another way to look at the Salesforce-Informatica deal is through the lens of data. The two companies have been circling each other for years—Salesforce nearly acquired Informatica in 2024 with a bid reportedly worth around $10 billion. If this latest deal goes through, it would significantly enhance Salesforce’s Data Cloud by giving it deeper access to enterprise data. That, in turn, would allow Salesforce to provide more advanced agentic support to the businesses that own and manage that information.
This matters because AI is only as good as the data it’s trained on and the data it can access in real time. By integrating Informatica’s capabilities, Salesforce wouldn’t just be acquiring a software company. It would be gaining a pipeline to cleaner, more structured enterprise data. That, in turn, could make its generative AI agents, such as those powered through its Agentforce platform, smarter, faster, and more contextually aware.
For AI agents to act autonomously and effectively inside enterprise environments, they need access to high-quality, well-managed data. This deal positions Salesforce to deliver on that promise, enabling its agents to tap into richer datasets with greater accuracy and speed, ultimately moving closer to the goal of intelligent software that can act on behalf of users across the business.
Informatica is no stranger to the AI game. Earlier this month, at the company’s annual data conference, it unveiled CLAIRE GPT, its CLAIRE Copilot, and generative AI blueprints for major cloud ecosystem partners.
Could this be a larger trend in which tech companies gobble up legacy data firms to help feed their AI investments?
This Week’s AI News
🏭 AI Trends and Industry Impact
- Americans to business: Take AI slow and do it right (Axios)
- Anthropic CEO Dario Amodei warns AI could wipe out half of all entry-level white-collar jobs in the next one to five years (Axios)
- AI may already be shrinking entry-level jobs in tech, new research suggests (TechCrunch)
- AI could consume more power than Bitcoin by the end of 2025 (The Verge)
🤖 AI Models and Technologies
- Mistral launches API for building AI agents that run Python, generate images, perform RAG, and more (VentureBeat)
- Mark Zuckerberg says Meta AI has 1 billion monthly active users (CNBC)
- DeepSeek R1-0528 arrives in powerful open source challenge to OpenAI o3 and Google Gemini 2.5 Pro (VentureBeat)
- OpenAI explores “sign-in with ChatGPT” for other apps (Mashable)
- Emotive voice AI startup Hume launches new EVI 3 model with rapid custom voice creation (VentureBeat)
- Researchers claim ChatGPT o3 bypassed shutdown in controlled test (BleepingComputer)
- Singapore’s AI push charts path toward localized models (Bloomberg)
- Sarvam AI’s backlash exposes the sad state of Indian AI (Analytics India Magazine)
✏️ Generative AI and Content Creation
- Anthropic launches a voice mode for Claude (TechCrunch)
- Perplexity’s new tool can generate spreadsheets, dashboards, and more (TechCrunch)
- Am I hot or not? People are asking ChatGPT for the harsh truth (Washington Post)
- Black Forest Labs’ Kontext AI models can edit pics as well as generate them (TechCrunch)
💰 Funding and Investments
- AI share of startup funding fluctuates sharply by stage (Crunchbase News)
- Grammarly secures $1 billion to build AI productivity platform (Reuters)
- Context gets $11 million to build an AI-powered office suite (TechCrunch)
- Spott’s AI-native recruiting platform scores $3.2 million to end hiring software chaos (VentureBeat)
- Superblocks raises $23 million to rein in the Wild West of vibe coding (Silicon Angle)
☁️ Enterprise AI Solutions
- MCP is RSS for AI: More use cases for Model Context Protocol (The New Stack)
⚙️ Hardware, Robotics, and Autonomous Systems
- Rabbit teases redesigned R1 UI after design god Jony Ive dumps on AI gadgets (Gizmodo)
- Hugging Face unveils two new humanoid robots (TechCrunch)
- The AI data center race is getting way more complicated (Quartz)
- China held the world’s first robot martial arts tournament, and I can’t think of a single thing that could possibly go wrong (PC Gamer)
- AI PCs will dominate by 2027, says Asus executive (Forbes)
- What the era of “sovereign AI” means for chip makers (The Wall Street Journal)
🔬 Science and Breakthroughs
- Ambience announces OpenAI-powered medical coding model that outperforms physicians (CNBC)
- ChatGPT for biology: A new AI whips up designer proteins with only a text prompt (SingularityHub)
- UnitedHealth CTO says AI investments can help a health care system that needs to be fixed (Fortune)
💼 Business, Marketing, Media, and Consumer Applications
- New York Times inks Amazon AI licensing pact, its first such deal (Variety)
- Meet the startup trying to build the Berkshire Hathaway for AI services (Upstarts Media)
- Video game companies have an AI problem: Players don’t want it (Bloomberg)
- In Dubai’s AI job market, your passport matters (Rest of World)
- Meta’s Llama AI team has been bleeding talent. Many top researchers have joined Mistral (Business Insider)
⚖️ Legal, Regulatory, and Ethical Issues
- Workday faces a collective action lawsuit alleging its job applicant screening tech prevented people over 40 from getting hired (CNN)
- Getty Images spending millions to battle a “world of rhetoric” in suit against Stability AI, CEO says (CNBC)
- Former Meta executive Nick Clegg says asking artists for use permission would “kill” the AI industry (The Verge)
- AI is eating data center power demand—and it’s only getting worse (Wired)
- The real cost of AI is being paid in deserts far from Silicon Valley (Rest of World)
💥 Disruption, Misinformation, and Risks
- 120 court cases have been caught with AI hallucinations, according to new database (Mashable)
- AI is perfecting scam emails, making phishing hard to catch (Axios)
🔎 Opinions, Analysis, and Editorials
- Google’s “world-model” bet: Building the AI operating layer before Microsoft captures the UI (VentureBeat)
- AI budgets are hot, IT budgets are not (Silicon Angle)
End Output
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