2024: The State of Generative AI in the Enterprise — from menlovc.com (Menlo Ventures)
The enterprise AI landscape is being rewritten in real time. As pilots give way to production, we surveyed 600 U.S. enterprise IT decision-makers to reveal the emerging winners and losers.

This spike in spending reflects a wave of organizational optimism; 72% of decision-makers anticipate broader adoption of generative AI tools in the near future. This confidence isn’t just speculative—generative AI tools are already deeply embedded in the daily work of professionals, from programmers to healthcare providers.

Despite this positive outlook and increasing investment, many decision-makers are still figuring out what will and won’t work for their businesses. More than a third of our survey respondents do not have a clear vision for how generative AI will be implemented across their organizations. This doesn’t mean they’re investing without direction; it simply underscores that we’re still in the early stages of a large-scale transformation. Enterprise leaders are just beginning to grasp the profound impact generative AI will have on their organizations.


Business spending on AI surged 500% this year to $13.8 billion, says Menlo Ventures — from cnbc.com by Hayden Field

Key Points

  • Business spending on generative AI surged 500% this year, hitting $13.8 billion — up from just $2.3 billion in 2023, according to data from Menlo Ventures released Wednesday.
  • OpenAI ceded market share in enterprise AI, declining from 50% to 34%, per the report.
  • Amazon-backed Anthropic doubled its market share from 12% to 24%.

Microsoft quietly assembles the largest AI agent ecosystem—and no one else is close — from venturebeat.com by Matt Marshall

Microsoft has quietly built the largest enterprise AI agent ecosystem, with over 100,000 organizations creating or editing AI agents through its Copilot Studio since launch – a milestone that positions the company ahead in one of enterprise tech’s most closely watched and exciting  segments.

The rapid adoption comes as Microsoft significantly expands its agent capabilities. At its Ignite conference [that started on 11/19/24], the company announced it will allow enterprises to use any of the 1,800 large language models (LLMs) in the Azure catalog within these agents – a significant move beyond its exclusive reliance on OpenAI’s models. The company also unveiled autonomous agents that can work independently, detecting events and orchestrating complex workflows with minimal human oversight.


Now Hear This: World’s Most Flexible Sound Machine Debuts — from
Using text and audio as inputs, a new generative AI model from NVIDIA can create any combination of music, voices and sounds.

Along these lines, also see:


AI Agents Versus Human Agency: 4 Ways To Navigate Our AI-Driven World — from forbes.com by Cornelia C. Walther

To understand the implications of AI agents, it’s useful to clarify the distinctions between AI, generative AI, and AI agents and explore the opportunities and risks they present to our autonomy, relationships, and decision-making.

AI Agents: These are specialized applications of AI designed to perform tasks or simulate interactions. AI agents can be categorized into:

    • Tool Agents…
    • Simulation Agents..

While generative AI creates outputs from prompts, AI agents use AI to act with intention, whether to assist (tool agents) or emulate (simulation agents). The latter’s ability to mirror human thought and action offers fascinating possibilities — and raises significant risks.

 

Skill-Based Training: Embrace the Benefits; Stay Wary of the Hype — from learningguild.com by Paige Yousey

1. Direct job relevance
One of the biggest draws of skill-based training is its direct relevance to employees’ daily roles. By focusing on teaching job-specific skills, this approach helps workers feel immediately empowered to apply what they learn, leading to a quick payoff for both the individual and the organization. Yet, while this tight focus is a major benefit, it’s important to consider some potential drawbacks that could arise from an overly narrow approach.

Be wary of:

  • Overly Narrow Focus: Highly specialized training might leave employees with little room to apply their skills to broader challenges, limiting versatility and growth potential.
  • Risk of Obsolescence: Skills can quickly become outdated, especially in fast-evolving industries. L&D leaders should aim for regular updates to maintain relevance.
  • Neglect of Soft Skills: While technical skills are crucial, ignoring soft skills like communication and problem-solving may lead to a lack of balanced competency.

2. Enhanced job performance…
3. Addresses skill gaps…

…and several more areas to consider


Another item from Paige Yousey

5 Key EdTech Innovations to Watch — from learningguild.com by Paige Yousey

AI-driven course design

Strengths

  • Content creation and updates: AI streamlines the creation of training materials by identifying resource gaps and generating tailored content, while also refreshing existing materials based on industry trends and employee feedback to maintain relevance.
  • Data-driven insights: Use AI tools to provide valuable analytics to inform course development and instructional strategies, helping learner designers identify effective practices and improve overall learning outcomes.
  • Efficiency: Automating repetitive tasks, such as learner assessments and administrative duties, enables L&D professionals to concentrate on developing impactful training programs and fostering learner engagement.

Concerns

  • Limited understanding of context: AI may struggle to understand the specific educational context or the unique needs of diverse learner populations, potentially hindering effectiveness.
  • Oversimplification of learning: AI may reduce complex educational concepts to simple metrics or algorithms, oversimplifying the learning process and neglecting deeper cognitive development.
  • Resistance to change: Learning leaders may face resistance from staff who are skeptical about integrating AI into their training practices.

Also from the Learning Guild, see:

Use Twine to Easily Create Engaging, Immersive Scenario-Based Learning — from learningguild.com by Bill Brandon

Scenario-based learning immerses learners in realistic scenarios that mimic real-world challenges they might face in their roles. These learning experiences are highly relevant and relatable. SBL is active learning. Instead of passively consuming information, learners actively engage with the content by making decisions and solving problems within the scenario. This approach enhances critical thinking and decision-making skills.

SBL can be more effective when storytelling techniques create a narrative that guides learners through the scenario to maintain engagement and make the learning memorable. Learners receive immediate feedback on their decisions and learn from their mistakes. Reflection can deepen their understanding. Branching scenarios add simulated complex decision-making processes and show the outcome of various actions through interactive scenarios where learner choices lead to different outcomes.

Embrace the Future: Why L&D Leaders Should Prioritize AI Digital Literacy — from learningguild.com by Dr. Erica McCaig

The role of L&D leaders in AI digital literacy
For L&D leaders, developing AI digital literacy within an organization requires a well-structured curriculum and development plan that equips employees with the knowledge, skills, and ethical grounding needed to thrive in an AI-augmented workplace. This curriculum should encompass a range of competencies that enhance technical understanding and foster a mindset ready for innovation and responsible use of AI. Key areas to focus on include:

  • Understanding AI Fundamentals: …
  • Proficiency with AI Tools: …
  • Ethical Considerations: …
  • Cultivating Critical Thinking: …
 

7 Legal Tech Trends To Watch In 2025 — from lexology.com by Sacha Kirk
Australia, United Kingdom November 25 2024

In-house legal teams are changing from a traditional support function to becoming proactive business enablers. New tools are helping legal departments enhance efficiency, improve compliance, and to deliver greater strategic value.

Here’s a look at seven emerging trends that will shape legal tech in 2025 and insights on how in-house teams can capitalise on these innovations.

1. AI Solutions…
2. Regulatory Intelligence Platforms…

7. Self-Service Legal Tools and Knowledge Management
As the demand on in-house legal teams continues to grow, self-service tools are becoming indispensable for managing routine legal tasks. In 2025, these tools are expected to evolve further, enabling employees across the organisation to handle straightforward legal processes independently. Whether it’s accessing pre-approved templates, completing standard agreements, or finding answers to common legal queries, self-service platforms reduce the dependency on legal teams for everyday tasks.

Advanced self-service tools go beyond templates, incorporating intuitive workflows, approval pathways, and built-in guidance to ensure compliance with legal and organisational policies. By empowering business users to manage low-risk matters on their own, these tools free up legal teams to focus on complex and high-value work.


 

 

Building the lawyer of the future — from jordanfurlong.substack.com by Jordan Furlong
Here’s my latest “Future Lawyer Starter Kit.” Tell me what you think.

Building upon this knowledge foundation, I suggest that future lawyers should develop the following ten human competencies (through a completely overhauled education, training, and licensing process, but that’s a topic for another day):

  1. Acting ethically
  2. Advocating and negotiating
  3. Demonstrating character
  4. Displaying empathy
  5. Exercising judgment
  6. Giving advice
  7. Reasoning legally
  8. Relating with people
  9. Resolving conflicts
  10. Solving problems
 

What DICE does in this posting will be available 24x7x365 in the future [Christian]

From DSC:
First of all, when you look at the following posting:


What Top Tech Skills Should You Learn for 2025? — from dice.com by Nick Kolakowski


…you will see that they outline which skills you should consider mastering in 2025 if you want to stay on top of the latest career opportunities. They then list more information about the skills, how you apply the skills, and WHERE to get those skills.

I assert that in the future, people will be able to see this information on a 24x7x365 basis.

  • Which jobs are in demand?
  • What skills do I need to do those jobs?
  • WHERE do I get/develop those skills?


And that last part (about the WHERE do I develop those skills) will pull from many different institutions, people, companies, etc.

BUT PEOPLE are the key! Oftentimes, we need to — and prefer to — learn with others!


 

The Edtech Insiders Generative AI Map — from edtechinsiders.substack.com by Ben Kornell, Alex Sarlin, Sarah Morin, and Laurence Holt
A market map and database featuring 60+ use cases for GenAI in education and 300+ GenAI powered education tools.


A Student’s Guide to Writing with ChatGPT— from openai.com

Used thoughtfully, ChatGPT can be a powerful tool to help students develop skills of rigorous thinking and clear writing, assisting them in thinking through ideas, mastering complex concepts, and getting feedback on drafts.

There are also ways to use ChatGPT that are counterproductive to learning—like generating an essay instead of writing it oneself, which deprives students of the opportunity to practice, improve their skills, and grapple with the material.

For students committed to becoming better writers and thinkers, here are some ways to use ChatGPT to engage more deeply with the learning process.


Community Colleges Are Rolling Out AI Programs—With a Boost from Big Tech — from workshift.org by Colleen Connolly

The Big Idea: As employers increasingly seek out applicants with AI skills, community colleges are well-positioned to train up the workforce. Partnerships with tech companies, like the AI Incubator Network, are helping some colleges get the resources and funding they need to overhaul programs and create new AI-focused ones.

Along these lines also see:

Practical AI Training — from the-job.beehiiv.com by Paul Fain
Community colleges get help from Big Tech to prepare students for applied AI roles at smaller companies.

Miami Dade and other two-year colleges try to be nimble by offering training for AI-related jobs while focusing on local employers. Also, Intel’s business struggles while the two-year sector wonders if Republicans will cut funds for semiconductor production.


Can One AI Agent Do Everything? How To Redesign Jobs for AI? HR Expertise And A Big Future for L&D. — from joshbersin.com by Josh Bersin

Here’s the AI summary, which is pretty good.

In this conversation, Josh Bersin discusses the evolving landscape of AI platforms, particularly focusing on Microsoft’s positioning and the challenges of creating a universal AI agent. He delves into the complexities of government efficiency, emphasizing the institutional challenges faced in re-engineering government operations.

The conversation also highlights the automation of work tasks and the need for businesses to decompose job functions for better efficiency.

Bersin stresses the importance of expertise in HR, advocating for a shift towards full stack professionals who possess a broad understanding of various HR functions.

Finally, he addresses the impending disruption in Learning and Development (L&D) due to AI advancements, predicting a significant transformation in how L&D professionals will manage knowledge and skills.


 

 

The State of Instructional Design, 2024 — from by Dr. Philippa Hardman
Four initial results from a global survey I ran with Synthesia

In September, I partnered with Synthesia to conduct a comprehensive survey exploring the evolving landscape of instructional design.

Our timing was deliberate: as we witness the rapid advancement of AI and increasing pressure on learning teams to drive mass re-skilling and deliver more with less, we wanted to understand how the role of instructional designers is changing.

Our survey focused on five key areas that we believed would help surface the most important data about the transformation of our field:

    1. Roles & Responsibilities: who’s designing learning experiences in 2024?
    2. Success Metrics: how do you and the organisations you work for measure the value of instructional design?
    3. Workload & Workflow: how much time do we spend on different aspects of our job, and why?
    4. Challenges & Barriers: what sorts of obstacles prevent us from producing optimal work?
    5. Tools & Technology: what tools do we use, and is the tooling landscape changing?
 

Career Cluster Appendix — from gettingsmart.com
New technology, global challenges and initiatives point to new pathways and new opportunities in our economies career clusters. The following resources highlight exemplars, entrepreneurial opportunities and high schools who are leading the way in pathway development and implementation. 

 



Google’s worst nightmare just became reality — from aidisruptor.ai by Alex McFarland
OpenAI just launched an all-out assault on traditional search engines.

Google’s worst nightmare just became reality. OpenAI didn’t just add search to ChatGPT – they’ve launched an all-out assault on traditional search engines.

It’s the beginning of the end for search as we know it.

Let’s be clear about what’s happening: OpenAI is fundamentally changing how we’ll interact with information online. While Google has spent 25 years optimizing for ad revenue and delivering pages of blue links, OpenAI is building what users actually need – instant, synthesized answers from current sources.

The rollout is calculated and aggressive: ChatGPT Plus and Team subscribers get immediate access, followed by Enterprise and Education users in weeks, and free users in the coming months. This staged approach is about systematically dismantling Google’s search dominance.




Open for AI: India Tech Leaders Build AI Factories for Economic Transformation — from blogs.nvidia.com
Yotta Data Services, Tata Communications, E2E Networks and Netweb are among the providers building and offering NVIDIA-accelerated infrastructure and software, with deployments expected to double by year’s end.


 

How to Level Up Your Job Hunt With AI Using AI to find, evaluate, and apply for jobs. — from whytryai.com by Daniel Nest

AI is best seen as a sparring partner that helps you through all stages of the job hunt.

Here are the ones I’ll cover:

  1. Self-discovery: What are you good at and what are your values?
  2. Upskilling: What gaps exist in your skillset and how can you close them?
  3. Job search: What existing jobs fit your profile and expectations?
  4. Company research: What can you learn about a specific company before applying?
  5. Application process: How do you tailor your CV and cover letter to the job?
  6. Job interview prepHow do you prepare and practice for job interviews?
  7. Feedback analysis: What insights can you gain from any feedback from potential employers?
  8. Decision and negotiation: How do you evaluate job offers and negotiate the best terms?

Now let’s look at each phase in detail and see how AI can help.

 

Along these same lines, see:

Introducing computer use, a new Claude 3.5 Sonnet, and Claude 3.5 Haiku

We’re also introducing a groundbreaking new capability in public beta: computer use. Available today on the API, developers can direct Claude to use computers the way people do—by looking at a screen, moving a cursor, clicking buttons, and typing text. Claude 3.5 Sonnet is the first frontier AI model to offer computer use in public beta. At this stage, it is still experimental—at times cumbersome and error-prone. We’re releasing computer use early for feedback from developers, and expect the capability to improve rapidly over time.


ZombAIs: From Prompt Injection to C2 with Claude Computer Use — from embracethered.com by Johann Rehberger

A few days ago, Anthropic released Claude Computer Use, which is a model + code that allows Claude to control a computer. It takes screenshots to make decisions, can run bash commands and so forth.

It’s cool, but obviously very dangerous because of prompt injection. Claude Computer Use enables AI to run commands on machines autonomously, posing severe risks if exploited via prompt injection.

This blog post demonstrates that it’s possible to leverage prompt injection to achieve, old school, command and control (C2) when giving novel AI systems access to computers.

We discussed one way to get malware onto a Claude Computer Use host via prompt injection. There are countless others, like another way is to have Claude write the malware from scratch and compile it. Yes, it can write C code, compile and run it. There are many other options.

TrustNoAI.

And again, remember do not run unauthorized code on systems that you do not own or are authorized to operate on.

Also relevant here, see:


Perplexity Grows, GPT Traffic Surges, Gamma Dominates AI Presentations – The AI for Work Top 100: October 2024 — from flexos.work by Daan van Rossum
Perplexity continues to gain users despite recent controversies. Five out of six GPTs see traffic boosts. This month’s highest gainers including Gamma, Blackbox, Runway, and more.


Growing Up: Navigating Generative AI’s Early Years – AI Adoption Report — from ai.wharton.upenn.edu by  Jeremy Korst, Stefano Puntoni, & Mary Purk

From a survey with more than 800 senior business leaders, this report’s findings indicate that weekly usage of Gen AI has nearly doubled from 37% in 2023 to 72% in 2024, with significant growth in previously slower-adopting departments like Marketing and HR. Despite this increased usage, businesses still face challenges in determining the full impact and ROI of Gen AI. Sentiment reports indicate leaders have shifted from feelings of “curiosity” and “amazement” to more positive sentiments like “pleased” and “excited,” and concerns about AI replacing jobs have softened. Participants were full-time employees working in large commercial organizations with 1,000 or more employees.


Apple study exposes deep cracks in LLMs’ “reasoning” capabilities — from arstechnica.com by Kyle Orland
Irrelevant red herrings lead to “catastrophic” failure of logical inference.

For a while now, companies like OpenAI and Google have been touting advanced “reasoning” capabilities as the next big step in their latest artificial intelligence models. Now, though, a new study from six Apple engineers shows that the mathematical “reasoning” displayed by advanced large language models can be extremely brittle and unreliable in the face of seemingly trivial changes to common benchmark problems.

The fragility highlighted in these new results helps support previous research suggesting that LLMs use of probabilistic pattern matching is missing the formal understanding of underlying concepts needed for truly reliable mathematical reasoning capabilities. “Current LLMs are not capable of genuine logical reasoning,” the researchers hypothesize based on these results. “Instead, they attempt to replicate the reasoning steps observed in their training data.”


Google CEO says more than a quarter of the company’s new code is created by AI — from businessinsider.in by Hugh Langley

  • More than a quarter of new code at Google is made by AI and then checked by employees.
  • Google is doubling down on AI internally to make its business more efficient.

Top Generative AI Chatbots by Market Share – October 2024 


Bringing developer choice to Copilot with Anthropic’s Claude 3.5 Sonnet, Google’s Gemini 1.5 Pro, and OpenAI’s o1-preview — from github.blog

We are bringing developer choice to GitHub Copilot with Anthropic’s Claude 3.5 Sonnet, Google’s Gemini 1.5 Pro, and OpenAI’s o1-preview and o1-mini. These new models will be rolling out—first in Copilot Chat, with OpenAI o1-preview and o1-mini available now, Claude 3.5 Sonnet rolling out progressively over the next week, and Google’s Gemini 1.5 Pro in the coming weeks. From Copilot Workspace to multi-file editing to code review, security autofix, and the CLI, we will bring multi-model choice across many of GitHub Copilot’s surface areas and functions soon.

 

From DSC:
Great…we have another tool called Canvas. Or did you say Canva?

Introducing canvas — from OpenAI
A new way of working with ChatGPT to write and code

We’re introducing canvas, a new interface for working with ChatGPT on writing and coding projects that go beyond simple chat. Canvas opens in a separate window, allowing you and ChatGPT to collaborate on a project. This early beta introduces a new way of working together—not just through conversation, but by creating and refining ideas side by side.

Canvas was built with GPT-4o and can be manually selected in the model picker while in beta. Starting today we’re rolling out canvas to ChatGPT Plus and Team users globally. Enterprise and Edu users will get access next week. We also plan to make canvas available to all ChatGPT Free users when it’s out of beta.


Using AI to buy your home? These companies think it’s time you should — from usatoday.com by Andrea Riquier

The way Americans buy homes is changing dramatically.

New industry rules about how home buyers’ real estate agents get paid are prompting a reckoning among housing experts and the tech sector. Many house hunters who are already stretched thin by record-high home prices and closing costs must now decide whether, and how much, to pay an agent.

A 2-3% commission on the median home price of $416,700 could be well over $10,000, and in a world where consumers are accustomed to using technology for everything from taxes to tickets, many entrepreneurs see an opportunity to automate away the middleman, even as some consumer advocates say not so fast.


The State of AI Report 2024 — from nathanbenaich.substack.com by Nathan Benaich


The Great Mismatch — from the-job.beehiiv.com. by Paul Fain
Artificial intelligence could threaten millions of decent-paying jobs held by women without degrees.

Women in administrative and office roles may face the biggest AI automation risk, find Brookings researchers armed with data from OpenAI. Also, why Indiana could make the Swiss apprenticeship model work in this country, and how learners get disillusioned when a certificate doesn’t immediately lead to a good job.

major new analysis from the Brookings Institution, using OpenAI data, found that the most vulnerable workers don’t look like the rail and dockworkers who have recaptured the national spotlight. Nor are they the creatives—like Hollywood’s writers and actors—that many wealthier knowledge workers identify with. Rather, they’re predominantly women in the 19M office support and administrative jobs that make up the first rung of the middle class.

“Unfortunately the technology and automation risks facing women have been overlooked for a long time,” says Molly Kinder, a fellow at Brookings Metro and lead author of the new report. “Most of the popular and political attention to issues of automation and work centers on men in blue-collar roles. There is far less awareness about the (greater) risks to women in lower-middle-class roles.”



Is this how AI will transform the world over the next decade? — from futureofbeinghuman.com by Andrew Maynard
Anthropic’s CEO Dario Amodei has just published a radical vision of an AI-accelerated future. It’s audacious, compelling, and a must-read for anyone working at the intersection of AI and society.

But if Amodei’s essay is approached as a conversation starter rather than a manifesto — which I think it should be — it’s hard to see how it won’t lead to clearer thinking around how we successfully navigate the coming AI transition.

Given the scope of the paper, it’s hard to write a response to it that isn’t as long or longer as the original. Because of this, I’d strongly encourage anyone who’s looking at how AI might transform society to read the original — it’s well written, and easier to navigate than its length might suggest.

That said, I did want to pull out a few things that struck me as particularly relevant and important — especially within the context of navigating advanced technology transitions.

And speaking of that essay, here’s a summary from The Rundown AI:

Anthropic CEO Dario Amodei just published a lengthy essay outlining an optimistic vision for how AI could transform society within 5-10 years of achieving human-level capabilities, touching on longevity, politics, work, the economy, and more.

The details:

  • Amodei believes that by 2026, ‘powerful AI’ smarter than a Nobel Prize winner across fields, with agentic and all multimodal capabilities, will be possible.
  • He also predicted that AI could compress 100 years of scientific progress into 10 years, curing most diseases and doubling the human lifespan.
  • The essay argued AI could strengthen democracy by countering misinformation and providing tools to undermine authoritarian regimes.
  • The CEO acknowledged potential downsides, including job displacement — but believes new economic models will emerge to address this.
  • He envisions AI driving unprecedented economic growth but emphasizes ensuring AI’s benefits are broadly distributed.

Why it matters: 

  • As the CEO of what is seen as the ‘safety-focused’ AI lab, Amodei paints a utopia-level optimistic view of where AI will head over the next decade. This thought-provoking essay serves as both a roadmap for AI’s potential and a call to action to ensure the responsible development of technology.

AI in the Workplace: Answering 3 Big Questions — from gallup.com by Kate Den Houter

However, most workers remain unaware of these efforts. Only a third (33%) of all U.S. employees say their organization has begun integrating AI into their business practices, with the highest percentage in white-collar industries (44%).

White-collar workers are more likely to be using AI. White-collar workers are, by far, the most frequent users of AI in their roles. While 81% of employees in production/frontline industries say they never use AI, only 54% of white-collar workers say they never do and 15% report using AI weekly.

Most employees using AI use it for idea generation and task automation. Among employees who say they use AI, the most common uses are to generate ideas (41%), to consolidate information or data (39%), and to automate basic tasks (39%).


Nvidia Blackwell GPUs sold out for the next 12 months as AI market boom continues — from techspot.com by Skye Jacobs
Analysts expect Team Green to increase its already formidable market share

Selling like hotcakes: The extraordinary demand for Blackwell GPUs illustrates the need for robust, energy-efficient processors as companies race to implement more sophisticated AI models and applications. The coming months will be critical to Nvidia as the company works to ramp up production and meet the overwhelming requests for its latest product.


Here’s my AI toolkit — from wondertools.substack.com by Jeremy Caplan and Nikita Roy
How and why I use the AI tools I do — an audio conversation

1. What are two useful new ways to use AI?

  • AI-powered research: Type a detailed search query into Perplexity instead of Google to get a quick, actionable summary response with links to relevant information sources. Read more of my take on why Perplexity is so useful and how to use it.
  • Notes organization and analysis: Tools like NotebookLM, Claude Projects, and Mem can help you make sense of huge repositories of notes and documents. Query or summarize your own notes and surface novel connections between your ideas.
 

Employers Say Students Need AI Skills. What If Students Don’t Want Them? — from insidehighered.com by Ashley Mowreader
Colleges and universities are considering new ways to incorporate generative AI into teaching and learning, but not every student is on board with the tech yet. Experts weigh in on the necessity of AI in career preparation and higher education’s role in preparing students for jobs of the future.

Among the 5,025-plus survey respondents, around 2 percent (n=93), provided free responses to the question on AI policy and use in the classroom. Over half (55) of those responses were flat-out refusal to engage with AI. A few said they don’t know how to use AI or are not familiar with the tool, which impacts their ability to apply appropriate use to coursework.

But as generative AI becomes more ingrained into the workplace and higher education, a growing number of professors and industry experts believe this will be something all students need, in their classes and in their lives beyond academia.

From DSC:
I used to teach a Foundations of Information Technology class. Some of the students didn’t want to be there as they began the class, as it was a required class for non-CS majors. But after seeing what various applications and technologies could do for them, a good portion of those same folks changed their minds. But not all. Some students (2% sounds about right) asserted that they would never use technologies in their futures. Good luck with that I thought to myself. There’s hardly a job out there that doesn’t use some sort of technology.

And I still think that today — if not more so. If students want good jobs, they will need to learn how to use AI-based tools and technologies. I’m not sure there’s much of a choice. And I don’t think there’s much of a choice for the rest of us either — whether we’re still working or not. 

So in looking at the title of the article — “Employers Say Students Need AI Skills. What If Students Don’t Want Them?” — those of us who have spent any time working within the world of business already know the answer.

#Reinvent #Skills #StayingRelevant #Surviving #Workplace + several other categories/tags apply.


For those folks who have tried AI:

Skills: However, genAI may also be helpful in building skills to retain a job or secure a new one. People who had used genAI tools were more than twice as likely to think that these tools could help them learn new skills that may be useful at work or in locating a new job. Specifically, among those who had not used genAI tools, 23 percent believed that these tools might help them learn new skills, whereas 50 percent of those who had used the tools thought they might be helpful in acquiring useful skills (a highly statistically significant difference, after controlling for demographic traits).

Source: Federal Reserve Bank of New York

 

Workera’s CEO was mentored by Andrew Ng. Now he wants an AI agent to mentor you. — from techcrunch.com by Maxwell Zeff; via Claire Zau

On Tuesday, Workera announced Sage, an AI agent you can talk with that’s designed to assess an employee’s skill level, goals, and needs. After taking some short tests, Workera claims Sage will accurately gauge how proficient someone is at a certain skill. Then, Sage can recommend the appropriate online courses through Coursera, Workday, or other learning platform partners. Through chatting with Sage, Workera is designed to meet employees where they are, testing their skills in writing, machine learning, or math, and giving them a path to improve.

From DSC:
This is very much akin to what I’ve been trying to get at with my Learning from the Living [AI-Based Class] Room vision. And as learning agents come onto the scene, this type of vision should take off!

 

Walt Disney’s Wisdom: Lessons for Learning & Development Leaders — from learningguild.com by David Kelly

Here are a few of my favorite [quotes], along with the valuable lessons they offer us in Learning and Development.

  • “Everyone has deadlines.”
  • “I believe in being an innovator.”
  • “Times and conditions change so rapidly that we must keep our aim constantly focused on the future.
  • “I can never stand still. I must explore and experiment.”
  • …and several other quotes.
 
© 2024 | Daniel Christian