Technology Report 2024: Technology meets the moment as AI delivers results

In 2024, the technology sector moved firmly into the AI phase of computing. Cloud service providers, enterprises, and technology vendors are spending more on AI than ever, and adoption rates are high. But skeptics are wary of AI’s return on investment. What explains the dissonance? Our work with clients suggests that AI, more than other technology disruptions, generates little value from deployment alone. Creating value with AI requires changes in the working processes of hundreds or thousands of employees. Companies need to conduct business diagnostics, redesign processes, set targets, and manage change as they deploy this technology. But early proof points from our client work are encouraging, showing that generative AI initiatives could be worth up to 20% of EBITDA.

Read More · Bain & Company

Do Customers Perceive AI-Written Communications as Less Authentic?

From Nike and Google to Coca-Cola and McDonald's, major brands are incorporating artificial intelligence (AI) into their advertising campaigns. But how do consumers feel about robots generating emotionally charged marketing content? That's the question a New York Institute of Technology professor raises in a new Journal of Business Research study.

Read More · Phys.org / New York Institute of Technology

Companies Had Fun Experimenting With AI. Now They Have to Show the Returns.

Business technology leaders are winding down two years of fast-paced artificial intelligence experiments inside their companies, and putting their AI dollars toward proven projects focused on return on investment.

Read More · Wall Street Journal

Generative AI's next Act: The future lies in Agent Led AI Applications

The most interesting layer for venture capital. ~20 application layer companies with $1Bn+ in revenue were created during the cloud transition, another ~20 were created during the mobile transition, and we suspect the same will be true here. 

A comprehensive take on the how the AI market will evolve from "software as a service" to "services as software" In this latest essay on the state of the Generative AI market, Sequoia Capital explores how the consolidation of the foundational LLM layer has set the stage for the race to scale these higher-order reasoning and agentic capabilities, and discuss a new generation of “killer apps” with novel cognitive architectures and user interfaces.

Read more: Sequoia Capital

So many new AI productivity tools. How do I know what's best for me?

OpenAI launched ChatGPT Canvas last week, adding yet another productivity tool to your AI toolbelt. Lots of people are comparing Canvas to Anthropic's Claude Artifacts, and Google’s NotebookLM. While they are each impressive in their own right, they serve different purposes. ChatGPT Canvas offers a collaborative workspace perfect for coding and writing, Claude Artifacts excels in creativity and nuanced editing, while NotebookLM shines in managing large volumes of information. Let’s break down how each tool fits specific needs and why they might be a good addition to your workflow.

Read more: Shelly Palmer

Five Steps to AGI from ChatGPT

Using models like GPT-4o or even Claude 3.5 Sonnet, you’d be forgiven for thinking we’re getting close to reaching the initial goal of ‘Artificial General Intelligence’, but a new report on OpenAI’s efforts from Bloomberg suggests we’re still some way off creating AGI. According to Bloomberg's unnamed sources, OpenAI has 5 steps to reach AGI and we're only just moving towards step two — the creation of "reasoners". These are models capable of performing problem-solving tasks as well as a human with a PhD and no access to a textbook.

Read more: TomsGuide