Is Your Company Behind? How Leaders Are Using Gen AI in 2025

Here is what’s new in the AI world.

The Top Ways Companies Are Leveraging Gen AI for Growth in 2025

A new look at how large American companies are using artificial intelligence reveals that the technology is no longer experimental; it's deeply embedded in your core operations, and the financial returns are beginning to materialize.

The report "Accountable Acceleration: Gen AI Fast-Tracks Into the Enterprise," produced by Wharton and GBK Collective, surveyed more than 800 senior leaders at substantial companies.

Now in its third year, the findings show that generative AI has rapidly evolved from a curiosity to an essential tool in your daily workflow.

Here’s What the Numbers Tell You

According to Wharton professor Stefano Puntoni, this isn't just hype: "The vibe is good. The vibe is that this technology is delivering positive results."

Your Biggest Challenge Isn’t Tech, It’s Your People

While you're seeing benefits, the report highlights a critical tension you're likely facing. As AI handles more tasks, especially entry-level work, 43% of leaders worry about declining skills proficiency across their organizations.

What This Means for Your Leadership

The successful companies are those focusing on human-AI collaboration rather than replacement. Your employees need training to work effectively with AI, and you need to develop new roles that leverage both human expertise and AI capabilities.

The report suggests 2026 will be an inflection point where organizations like yours will shift from experimentation to performance at scale.

Your focus now should be on building the human capital infrastructure to support this transition, ensuring your team develops the skills to complement AI rather than compete with it.

The message is clear: AI is delivering value in your organization, but your long-term success depends on how well you integrate this technology with your human talent.

True integration isn't just about training people to use AI; it's about building AI that seamlessly integrates into your people's workflows. This is the core of TowardsMCP.

We provide the platform that connects your AI directly to your company's tools, data, and systems, transforming it from a passive chatbot into an active, capable teammate that amplifies your team's unique skills. It’s the missing layer that allows human and machine intelligence to work as one.

With 61% of Firms Using GenAI, CHROs Face Rising CEO Pressure to Cut Costs

You are likely facing unprecedented pressure from your CEO to deliver cost savings, driven by the rapid implementation of generative AI across your organization.

The C-Suite's AI Mandate

The executive suite is increasingly viewing AI as a primary lever for efficiency. Your CEO is demanding clarity on how automation will reduce structural costs, while your CFO is likely questioning whether AI can trim HR headcount.

As a CHRO, you are caught in the middle, under pressure to demonstrate how AI can handle operational tasks, freeing your team to focus on strategic initiatives.

The Scale of the Shift

The data reveals the staggering pace of this transformation. Gartner projects that 50% of current HR tasks will be automated or handled by AI agents by 2030.

This is not a distant future; a separate survey shows that in the past year alone, 27% of organizations have already redefined roles due to AI, and 24% have redeployed employees as automation creates redundancies.

Navigating the Human Capital Challenge

A critical challenge you face is the tendency of some executives to overestimate AI's ability to replace human capability. The key is to help your organization rethink work design, focusing on scenarios where human skills and AI tools complement each other.

Gartner recommends adopting a "now-next" talent strategy that maximizes your current workforce's performance while planning for more profound AI-driven changes.

Broader Organizational Strains

This AI acceleration coincides with other significant pressures. A majority of CHROs (64%) report that their leaders lack the mindset to guide teams through continual change.

Furthermore, the "employment deal" is tilting, with employees facing longer hours, heavier workloads, and reduced flexibility, even as only 47% of CHROs believe their culture drives the necessary performance.

To succeed in 2026, you must reset priorities by building AI-enabled operating models, clarifying your talent strategy, and strengthening leadership capabilities.

Your role is evolving from traditional HR management to architecting a new, resilient partnership between your human workforce and intelligent technology.

This evolution hinges on a single, critical asset: trusted, unified, and actionable data. You cannot build a resilient human-tech partnership on a foundation of siloed, inconsistent, or low-quality information.

DataManagement.AI provides the essential data fabric that empowers your entire organization, ensuring your HR systems, AI tools, and business intelligence all operate from a single source of truth.

It’s the platform that turns data into your most strategic advantage for workforce planning and AI integration.

Unlock Privacy and Power: The Easy Guide to Local Open-Source AI

You might be wondering why you'd ever want to run an open-source AI model on your home computer when you can just use ChatGPT.

The reasons are more compelling than you think, and with free models that are now both powerful and easy to use, there's never been a better time to try.

Here’s why running your own AI beats a $20/month subscription:

Getting Started is Surprisingly Simple

The technical barrier has collapsed. With user-friendly software, you don't need to be a developer. If you have a fairly recent computer, you can do this:

• A Windows/Linux PC with 8GB of video memory (VRAM) is great, and some models run on just 4GB.

• Any Apple Mac with an M-series chip from the last few years will work perfectly.

The entire setup boils down to one simple choice: do you prefer clicking buttons or typing commands?

Your Two Best Options: LM Studio vs. Ollama

Two platforms dominate, and they cater to different styles:

1. LM Studio: The Clickable Interface (Best for Beginners)

This is your go-to if you want a smooth, graphical experience that feels like using a regular app. You simply:

• Download the app from lmstudio.ai.

• Browse a built-in library of AI models and click to install.

• Start chatting in an interface that looks just like ChatGPT.

2. Ollama: The Power User's Command Line

Choose this if you're comfortable with typing commands and want maximum flexibility. You install it via a terminal and control everything with text commands. It's lightweight and perfect for automation.

Our recommendation: Start with LM Studio. It’s the easiest way to get your feet wet.

Your Step-by-Step Guide to LM Studio

1. Download and Install: Go to the LM Studio website, download the installer (about 540MB), and run it. When it asks, pick "developer" as your profile to see all options.

2. Check Your VRAM: This is your computer's "AI muscle."

   • On Windows: Press Ctrl+Alt+Delete, open Task Manager, click the "Performance" tab, and select your GPU. Look for "Dedicated GPU Memory."

   • On a Mac: Click the Apple logo > "About This Mac." Your "Memory" (RAM) is also your VRAM.

3. Download Your First AI Model: Click the magnifying glass icon in LM Studio and search for a model. Great starting points are:

   • Qwen2.5 7B: Excellent for general knowledge and reasoning.

   • DeepSeek Coder 7B: Perfect if you want help with programming.

   • Start with a 7-billion parameter model. If it's too slow, try a 3B model; if it runs well, you can later try a larger 13B model.

Giving Your AI Superpowers with MCP

By default, your local AI is a genius in a bubble; it doesn't know today's news or the weather. You can fix that with Model Context Protocol (MCP) servers, which are like bridges that give your AI access to the internet, your files, and other services.

LM Studio has built-in support for MCP, allowing your private AI to search the web or read documents without any data ever being sent to a corporation.

Our Top Model Picks for Your Machine

You can find all of these by searching directly within LM Studio. The best part? You can test them out, and if you don't like one, just delete it and try another.

The technology is ready, the software is free, and your computer is probably powerful enough. All that's left is for you to take control and try it.

From Darling to Dud? Perplexity's 'Most Likely to Flop' Award Rattles the AI Scene

Recent sentiment in Silicon Valley suggests the tide may be turning for some high-flying AI startups. In an informal survey of over 300 tech insiders in San Francisco, Perplexity, the AI search startup challenging Google, was identified as the most likely billion-dollar AI company to fail.

OpenAI ranked second in this concerning assessment.

Investor Mood Shifts Against AI Challengers

The survey results signal a notable shift in investor perspective. While AI startups like Perplexity were once seen as potential threats to Google's dominance, the current mood suggests growing skepticism about their long-term viability.

Perplexity's response to the survey was terse, with a spokesman calling it "the judgmental valley conference."

OpenAI's Position Despite Market Challenges

OpenAI's second-place ranking comes despite ChatGPT maintaining market leadership, even as it faces increased competition from Google's Gemini and other rivals.

Both companies have been expanding beyond their core products. Perplexity with its AI browser and OpenAI with Atlas browser, Sora social app, and new group chat features.

Growing Concerns About AI Valuation Bubble

The survey reflects broader concerns about an AI industry bubble. Investors are questioning how startups can justify massive valuations without clear paths to profitability.

Even industry leaders like Sam Altman and Mark Zuckerberg have acknowledged the possibility of an AI bubble while maintaining optimism about the technology's potential.

The valuation debate became particularly pointed when investor Brad Gerstner questioned how OpenAI could justify $1.4 trillion in spending commitments against $13 billion in revenue.

Meanwhile, Perplexity's own valuation trajectory, soaring from $14 billion to $50 billion in just months through successive funding rounds, exemplifies the rapid inflation that's fueling bubble concerns.

The survey results suggest that after years of exuberance, the market may be entering a more cautious phase regarding AI startup valuations and business models.

Your opinion matters!

Hope you loved reading our piece of newsletter as much as we had fun writing it. 

Share your experience and feedback with us below ‘cause we take your critique very critically. 

Thank you for reading

-Shen & Towards AGI team