Josh Bersin:2024: The Year That Changes Business Forever (Podcast)The podcast "2024: The Year That Changes Business Forever" by Josh Bersin explores anticipated transformations in business by 2024. It highlights the impact of AI, labor shortages, and evolving organizational structures. The podcast delves into the 2023 economic performance, changes in employee engagement, and the necessity for businesses to adapt strategically. It emphasizes a shift towards dynamic, flatter organizations and the critical role of systemic HR practices in shaping future business landscapes.
Josh Bersin探讨了2024年企业预期的转型。这些转型由AI的应用、劳动力短缺和组织结构的变化驱动。播客讨论了2023年的经济表现、员工参与度的变化以及企业为应对未来挑战所需的适应策略。它强调了向动态、扁平化组织的转变和系统性人力资源实践在塑造未来商业环境中的重要作用。
In this podcast I recap 2023 and discuss the big stories for 2024, and to me this year is a tipping point that changes business forever. Why do I say this? Because we’re entering a world of labor shortages, redesign of our companies, and business transformation driven by AI. We’ll look back on 2024 and realize it was a very pivotal year.
(Note: In mid-January we’re going to be publishing our detailed predictions report. This article is an edited transcript of this week’s podcast, so it reads like a conversation.)
Podcast Begins:
Interestingly, the entire year 2023 people were worried about a recession and it didn’t happen. In fact, economically and financially, we had a very strong year. Inflation in the United States and around the world went down. We did have to suffer rising interest rates, and that was a shock, but it was long overdue.
I really think the problem we experienced is we had low interest rates for far too long, encouraging speculative investment. Now that the economy is more rational, consumer demand is high, the business environment is solid, and the stock market is performing well. The Nasdaq is almost at an all time high, the seven super stocks did extremely well: the big tech companies, the big retailers, the oil companies, many of the consumer luxury goods companies did extremely well. And the only companies that didn’t do well were the companies that couldn’t make it through the transformation that’s going on.
On the cultural front we had the Supreme Court overturning affirmative action in education, which led to a political backlash on diversity and inclusion. The woke mind virus by Elon Musk and similar discussions further pushed back DEI programs, which has made chief diversity officers life difficult. We’re living through two wars, which have been very significant for many companies. I know a lot of you have closed down operations in Russia, and anybody doing business in Israel is having a tough time. And we’ve had this continuous period where every piece of data about employee engagement shows that employees are burned out, tired, stressed. They feel that they’re overworked.
Despite this employee sentiment, wages went up by over 5% and people who changed jobs saw raise wages of 8% or more. The unemployment rate is very low so there are a lot of jobs. You could ask yourself, why are people stressed?
I think it’s a continued overhang of the pandemic: the remote work challenges, the complexities and inconsistencies in hybrid work. And something else: the younger part of the workforce, those who are going to be living a lot longer than people who are baby boomers, are basically saying I don’t really want to kill myself just to get ahead. I want to have a life. I want to quietly quit. If my company don’t take care of me, I’m going to work my wage, meaning I’m going to work as hard as I’m paid, no more than that. And that mentality has created an environment for the four-day work week, which I think is coming quicker than you realize. And unions, which are politically in favor, are rising at an all time increase in about 25, 30 years.
Inflation and the need to raise wages to attract talent leads to pay equity problems. This domain is more complex than you think. You can read about it in our research and in 2024 it belongs on your list. 2024 will also see enormous demand for career reinvention, career development, growth programs, coaching, mentorship, allyship and support amongst the younger part of the workforce. And that means that if you’re in retail, healthcare, hospitality, or one of the other industries that hires younger people you have to accommodate this tremendous demand for benefits. These are things that became very clear in 2023.
But let’s talk about the elephant in the room: the biggest thing that happened in 2023 was AI.
AI has transformed the conversations we have about everything from media to publishing to HR technology to recruiting to employee development to employee experience. As you probably know, I’m very high on AI. I think it’s going to have a huge transformational effect on our companies, our jobs, our careers, and our personal lives. AI will improve our health, our ability to learn, the way we consume news (note that the NYT just sued OpenAI and Microsoft for copyright infringement). Almost every part of our life will be transformed by AI.
I know from our conversations that most of you are trying to understand it and see where it fits. And many of you have been told by your CEO, “we need an AI strategy for the company as well as in HR.” And the AI strategy in HR is one thing, but the bigger topic is the rest of the company. So HR is going to have to be a part of this transformation: the new roles, jobs, rewards, and skills we need.
This year I’m very excited that we introduced Galileo™, which about 500 or so of you have been using. We’re going to launch the corporate version for everybody in the corporate membership in February, so corporate members stay tuned (or join). Galileo brings AI to HR in an easy-to-use, safe, and high-value way, so it will help you get your strategy together. It’s basically ready to go. Then later in the year we’ll launch a version to the JBA community and more. AI, despite all the fear-mongering, is already a very positive technology.
Where are we going next? Well as the title of this article states, I think this is the year that changes business forever. And I’m not trying to be hyperbolic, I really see a tipping point. Let me give you the story.
For about a decade I’ve been writing about the flattening of organizations, breaking down of hierarchies, creating what I used to call the networked organization. And this is now mainstream and we’ve decided to call it the Dynamic Organization.
And what we mean by this, as you read about in the Dynamic Organization research or in the Post-Industrial Age study, is that the functional hierarchies of jobs, careers, organizations and companies are being broken down for really good reasons.
The reason we have functional hierarchies, job levels and siloed business functions is because they’re patterned after the industrial age when companies made money by selling products and services at scale. The automobile industry, the oil and gas industry, the manufacturing industries, the CPG industries, even the pharmaceutical companies are essentially building things, bringing them to market, launching them, selling them, and distributing them in a linear chain. And that “scalable industrial business model” is how we designed our organizations.
So we built large organizations for R&D, large organizations for product management and product design and packaging, large organizations for marketing, large organizations for sales, large organizations for business development and distribution, supply chain, and so on (including Finance and HR). And all these ten or fifteen business functions had their own hierarchies. So you, as an employee, worked your way up those hierarchies. When I graduated from college in 1978 as an engineer, I went into one of those hierarchies.
For each employee you were an engineer, a salesperson, a marketing manager, or whatever and you worked your way up the pyramid. And at some point in your career you crossed over and did other things, but that was fairly unusual. That wasn’t really the career path. You worked about 35-40 years in that profession and then you retired.
And a lot of companies had another construct: management and labor. Management decided “what to do” and labor “did it.”
And all of these designs helped us build most of the HR practices we use today, including hiring, pay, performance management, succession, career management, goal setting, leadership development, and on and on. Today, if you look at how the most valued companies in the world, they don’t operate this way any more. Why? Because it slows them down like molasses. If you have to traverse a functional hierarchy to come up with a new idea it takes months or years to create something new.
Today value is created through innovation, time to market, closeness to customers, and unique and high-value offerings. The “hierarchy” wasn’t designed for this at all.
Here are a few dogmas to consider. We used to think that all new ideas come out of R&D. That’s crazy. Of course R&D is important, but some of the most innovative companies in the world don’t even have R&D departments, they have product teams. The Research Department at Microsoft didn’t even invent AI, the company had to partner with OpenAI, a company that has less than a thousand employees.
Here’s another one to consider. Deloitte consultants used to talk about “innovation at the edge,” otherwise known as “skunk works.” We used to advise clients to “separate the new ideas from the scale business” so they new ideas don’t get crushed or ignored. Well today all the new ideas come from the operating businesses, and we iterate in a real-time way. So there’s another industrial organization structure that just no longer applies.
So what we’ve been going through in the dynamic organization, and we’ve studied this in detail, is that we’ve got to design our companies to be flatter. We’ve got to simplify the job titles and descriptions so people can move around. We have to organize people into cross functional teams, we have to motivate and train people to work across the functional silos. We have to build agile working groups, we have to redo performance management around teams and projects, not around individual goals and cascading goals. We need to build pay equity into the system so you’re paid fairly regardless of where you started.
Let’s talk about pay. One of the problems with the hierarchy is you get a raise every year based on your performance appraisal. And after a few years your pay may have been quite a bit different than somebody sitting next to you simply because of your appraisals. But you may not be delivering any more than them. That wasn’t fair.
If you came into the company with a background in marketing, you made less money than somebody who came into the company with a background in engineering. But five years later you might be doing the same stuff but making different amounts of money. And then there’s gender bias, age bias, and other non-performance factors. In a “skills meritocracy,” as we call it, pay equity has to get fixed.
We’ve got to have developmental careers and talent marketplaces and open job opportunities and mentoring for people. And these people practices are the facilitation of becoming more dynamic. And the problem of not being dynamic is what happened at Salesforce, Meta, and other tech companies last year. Salesforce hired thousands of salespeople during the last upcycle after the pandemic, and then a year later laid most of them off. Meta did the same thing. Google’s probably next.
These companies, operating in the industrial mindset, thought that the only way to grow is to hire more salespeople, more engineers, or more marketing folks. But the quantity of people in one of these business functions doesn’t necessarily drive growth and profitability. What matters is how they work together and what they do, not how many of them there are.
This old idea that we’re going to grow the company by hiring, hiring, hiring is gone. It doesn’t work anymore. It’s still a part of the growth part of the company, you’re always hiring to replace people, to bring new skills, et cetera, and to bring new perspectives. But in a dynamic organization, a lot of the growth comes from within. People grow too.
Even the word growth mindset has become overused. We need to have an organizational growth mindset so that we can grow as an organization. A great example of this is Intel. Intel lost their way in the manufacturing of semiconductors and also in the R&D. Now they’re reinventing themselves internally and their stock is skyrocketing. They didn’t hire some guru to tell them what to do, they know what to do. They just need to get around to doing it.
Google has more AI engineers than OpenAI, Anthropic, and all the other little guys put together, but they didn’t execute well. Now they’re executing better. They brought their AI teams together into cross-functional groups and they’re sharing IP from YouTube with other business areas. I bet they stomp many of the others in AI once they get it going. That’s part of being a dynamic organization.
You as HR people know better than anybody how dysfunctional it is when there are multiple groups in the company doing competing things and they’re not working together because they don’t know about each other, or they don’t talk to each other. There’s no cross fertilization or they’re protecting their turf. All of these are the things that get in the way of being a dynamic organization.
And the reason it’s relevant in the next year is this has taken hold. Things like talent marketplaces and career pathways and skills-based organizations, skills based hiring, skills based pay, skills based careers, skills based development, et cetera… these are not just HR fads, they’re solutions to this big shift: making companies more dynamic. Despite their value in the past, hierarchical stove-piped companies don’t operate very well anymore.
Now this isn’t an A-B switch type of thing. This is an evolution, but it’s taking place very quickly. And the reason we came up with this concept of Systemic HR is we in HR have to do the same thing. The HR function itself operates in silos. We’ve got the recruiting group, the DEI group, the Comp group, the L&D group, the business partners, the group that does compliance, the group that worries about wellbeing. We’ve got somebody over here is doing an EX project, somebody over there is doing a data management project, a people analytics group.
Okay. Those are all great functional areas that belong in HR. But if they’re not working together on the problems that the company has, and I mean the big problems, growth, profitability, productivity, M&A, etc., then who cares? Then you’re at level one or level two in systemic HR. We built the Systemic HR initiative around business problems. And that’s how we came up with the new HR operating model (read more details here or view the video overview).
I think Systemic HR will be a very big deal for 2024, and there are many reasons. Not only are we living in a labor shortage but there’s another accelerant, and that is AI. For those of you that have used Galileo, and I hope you all get a chance to use it this year, it’s absolutely unbelievable how AI can pull together information, data, text from many sources in the company and make sense of what your company is doing.
You know as well as I do, if you’ve worked in sales, if you’ve worked in marketing, if you worked in finance, these are siloed groups. Few companies have a truly integrated data management system for all of their customer data match to their sales, data match to their revenue, data match to their marketing. Customer data platforms are a idea, but it doesn’t really happen very often, and it takes tens to hundreds of millions of dollars and many, many systems to do that. Well, AI does this almost automatically.
So when you pull together a tool like Galileo, and you use our research as part of the corpus, and you add data about employee turnover, for example, in your company, or pay variations, you’ll see the relationship between pay and turnover just by asking a question. You don’t have to go spend months doing an analysis and trying to figure out if the analysis is any good. And that’s happening all over the company in sales and customer service and R&D and marketing – everywhere.
So this more integrated, dynamic organization is happening before your eyes. In 2024, this is the context for almost everything we’re going to be working on now.
The other context is the labor market, which is going to be very tough. You’ve read about from us and others about how tight the labor market is now. Unemployment in the United States is 3.8%, and it’s not going to get much better. Even if we do have a recession, which is questionable, there aren’t enough people to hire. The fertility rate is low, and even if every company gives employees fertility benefits and they all have babies, it will take twenty years for these people to go to work. So all of the developed countries: US, UK, Canada, Germany, Japan, the Nordics, China, Russia, the fertility rate has been low for a long time. The World Bank sees working population shrinking within ten years in almost every developed economy.
Since hiring is going to get harder and we’ll see fewer and fewer working people, companies have to be much more integrated in hiring. And we all have to look the Four R’s: Recruit, Retain, Reskill, Redesign. This puts HR in the middle of a lot of job redesign, career reinvention, and a serious look at developing skills, not hiring skills, and using the tools we have as hr professionals to help the organization improve productivity without just hiring and hiring and hiring.
I measure the success of companies by two things. One is their endurance: how well have they fared over ups and downs? The second is their revenue per employee. Companies with low revenues per employee tend to be poorly managed companies relative to their peers. Of course there’s a lot of industry differences.
When we went through our GWI industry work: healthcare, consumer goods, pharma, banking, we could see the high performing companies were very efficient on a headcount basis. And we found out these companies are actually implementing Systemic HR practices.
The other driver that we’re living in a service economy. Interestingly enough, in the United States, more than 70% of our GDP is now services. So the people you have, the humans in your company, are the product. And if you’re not getting good output per dollar of revenue per human, you’re not running the company very well.
And this leads to many management topics.
How are we going to build early and mid-level leaders?
How can we rethink what employees really need? The topics of employee engagement and employee experience are really 25 to 30 years old. They need a massive update.
How are we going to implement AI in L&D and replace a lot of these old systems that everybody kind of hates, but we’re stuck with?
What’s going on with the ERP vendors and what role will they play as we replace our HR tech with AI powered systems?
How will we implement scalable talent intelligence? In a world of labor shortages talent intelligence becomes even more important, whether you think of it for sourcing and recruiting or an internal mobility or just a strategic planning initiative.
How do we all get comfortable with AI?
And then there’s this issue of Systemic HR and developing your team, your function, your operating model to be more adaptive and more dynamic.
So I look back on 2023 I feel it was one of the most fascinating and fun and enriching years that I’ve had. I am always amazed and impressed and energized by you, by you guys who were out there on the firing lines, dealing with these complex issues and companies with old technologies and all sorts of changes going on and how you’re adapting. I continue to be more impressed and more excited about the HR profession every year. I think a lot of people who aren’t in HR think we do a lot of compliance and administration stuff and we fire people. That is the tiniest part of what we do.
2024 is going to be an important year. You as an HR professional are going to have to learn a lot of things. You’re going to learn about Systemic HR issues, you’re going to learn about AI, and you’re going to learn to be a consultant.
There’s no question in my mind that over the next decade or two dynamic organization management is going to become a bigger and bigger issue – how we manage people and companies. And I don’t mean manage like supervise, I mean develop, move, retain, pay, et cetera, culture, all of those things.
I leave 2023 very energized about what’s to come with AI. And if you’re afraid of AI, just take a deep breath and relax. It’s not going to bite you. There’s nothing evil here. It’s a data driven system. If you don’t have your data act together, you’re not going to get a lot of good value out of AI.
I talked to Donna Morris at Walmart last week; I talked to Nickle LaMoreaux at IBM; and I talked with the senior HR leaders at Microsoft. They’re all seeing huge returns on investment from the early implementations, and seeing hundreds of use cases. We’re going to have a lot of new tools and lots of vendor shakeout. (Check out what SAP is up to and where Workday is going.)
Stay tuned for our big Predictions report coming out in mid January. That report is my chance to give you some deep perspectives on where I think things are going, recap things that have happened over the last couple of years, and give you some perspectives for the year ahead.
As always we would be more than happy to walk through these things with your team.
I hope you have a really nice holiday season and you take a deep breath.
The world is never perfect. It’s never been perfect. It wasn’t perfect in the past. It won’t be perfect in the future.
But the environment you live in and the environment that you create can be enriching, enjoyable, productive, and healthy, and fun if you decide. And I think we all have the opportunity to make those decisions.
It has been a pleasure and an honor for me to serve and work with you this last year, and I’m really looking forward to an amazing 2024 together.
–END OF PODCAST–
Irresistible: The Seven Secrets of the World’s Most Enduring, Employee-Focused Organizations
AI
2023年12月30日
AI
人工智能正在以比我预期更快的速度改变企业学习AI Is Transforming Corporate Learning Even Faster Than I Expected在《AI正在比我预想的更快地改变企业学习AI Is Transforming Corporate Learning Even Faster Than I Expected》这一文中，Josh Bersin强调了AI对企业学习和发展（L&D）领域的革命性影响。L&D市场价值高达3400亿美元，涵盖了从员工入职到操作程序等一系列活动。传统模型正在随着像Galileo™这样的生成性AI技术的发展而演变，这改变了内容的创建、个性化和传递方式。本文探讨了AI在L&D中的主要用例，包括内容生成、个性化学习体验、技能发展，以及用AI驱动的知识工具替代传统培训。举例包括Arist的AI内容创作、Uplimit的个性化AI辅导，以及沃尔玛实施AI进行即时培训。这种转型是深刻的，呈现了一个AI不仅增强而且重新定义L&D策略的未来。
在受人工智能影响的所有领域中，最大的变革也许发生在企业学习中。经过一年的实验，现在很明显人工智能将彻底改变这个领域。
让我们讨论一下 L&D 到底是什么。企业培训无处不在，这就是为什么它是一个价值 3400 亿美元的市场。工作中发生的一切（从入职到填写费用账户再到复杂的操作程序）在某种程度上都需要培训。即使在经济衰退期间，企业在 L&D 上的支出仍稳定在人均 1200-1500 美元。
然而，正如研发专业人士所知，这个问题非常复杂。有数百种培训平台、工具、内容库和方法。我估计 L&D 技术空间的规模超过 140 亿美元，这甚至不包括搜索引擎、知识管理工具以及 Zoom、Teams 和 Webex 等平台等系统。多年来，我们经历了许多演变：电子学习、混合学习、微型学习，以及现在的工作流程中的学习。
生成式人工智能即将永远改变这一切。
考虑一下我们面临的问题。企业培训并不是真正的教学，而是创造一个学习的环境。传统的教学设计以教师为主导，以过程为中心，但在工作中常常表现不佳。人们通过多种方式学习，通常没有老师，他们寻找参考资料，复制别人正在做的事情，并依靠经理、同事和专家的帮助。因此，必须扩展传统的教学设计模型，以帮助人们学习他们需要的东西。
输入生成人工智能，这是一种旨在合成信息的技术。像Galileo™这样的生成式人工智能工具 可以以传统教学设计师无法做到的方式理解、整合、重组和传递来自大型语料库的信息。这种人工智能驱动的学习方法不仅效率更高，而且效果更好，能够在工作流程中进行学习。
早期，在工作流程中学习意味着搜索信息并希望找到相关的东西。这个过程非常耗时，而且常常没有结果。生成式人工智能通过其神经网络的魔力，现在已经准备好解决这些问题，就像 L&D 的瑞士军刀一样。
这是一个简单的例子。我问Galileo™（该公司经过 25 年的研究和案例研究提供支持）：“我该如何应对总是迟到的员工？请给我一个叙述来帮助我？” 它没有带我去参加管理课程或给我看一堆视频，而是简单地回答了问题。这种类型的互动是企业学习的大部分内容。
让我总结一下人工智能在学习与发展中的四个主要用例：
生成内容：人工智能可以大大减少内容创建所涉及的时间和复杂性。例如，移动学习工具Arist拥有AI生成功能Sidekick，可以将综合的操作信息转化为一系列的教学活动。这个过程可能需要几周甚至几个月的时间，现在可以在几天甚至几小时内完成。
我们在Josh Bersin 学院使用 Arist ，我们的新移动课程现在几乎每月都会推出。Sana、Docebo Shape和以用户为中心的学习平台 360 Learning 等其他工具也同样令人兴奋。
个性化学习者体验：人工智能可以帮助根据个人需求定制学习路径，改进根据工作角色分配学习路径的传统模型。人工智能可以理解内容的细节，并使用该信息来个性化学习体验。这种方法比杂乱的学习体验平台（LXP）有效得多，因为LXP通常无法真正理解内容的细节。
Uplimit是一家致力于构建人工智能平台来帮助教授人工智能的初创公司，它正在使用其Cobot和其他工具为学习人工智能的技术专业人员提供个性化的指导和技巧。Cornerstone 的新 AI 结构按技能推荐课程，Sana 平台将 Galileo 等工具与学习连接起来，SuccessFactors 中的新 AI 功能还为用户提供了基于角色和活动的精选学习视图。
识别和发展技能：人工智能可以帮助识别内容中的技能并推断个人的技能。这有助于提供正确的培训并确定其有效性。虽然许多公司正在研究高级技能分类策略，但真正的价值在于可以通过人工智能识别和开发的细粒度、特定领域的技能。
人才情报领域的先驱者Eightfold、Gloat和SeekOut可以推断员工技能并立即推荐学习解决方案。实际上，我们正在使用这项技术来推出我们的人力资源职业导航器，该导航器将于明年初推出。
用知识工具取代培训：人工智能在学习与发展中最具颠覆性的用例也许是完全取代某些类型培训的潜力。人工智能可以创建提供信息和解决问题的智能代理或聊天机器人，从而可能消除对某些类型培训的需求。这种方法不仅效率更高，而且效果更好，因为它可以在个人需要时为他们提供所需的信息。
沃尔玛今天正在实施这一举措，我们的新平台 Galileo 正在帮助万事达卡和劳斯莱斯等公司在无需培训的情况下按需查找人力资源信息和政策信息。LinkedIn Learning 正在向 Gen AI 搜索开放其软技能内容，很快 Microsoft Copilot 将通过 Viva Learning 找到培训。
这里潜力巨大
在我作为分析师的这些年里，我从未见过一种技术具有如此大的潜力。人工智能将彻底改变 L&D 格局，重塑我们的工作方式，以便 L&D 专业人员可以花时间为企业提供咨询。
L&D 专业人员应该做什么？花一些时间来了解这项技术，或者参加Josh Bersin 学院的一些新的人工智能课程以了解更多信息。
随着我们继续推出像伽利略这样的工具，我知道你们每个人都会对未来的机会感到惊讶。L&D 的未来已经到来，而这一切都由人工智能驱动。
AI
2023年12月13日
AI
微软首席人力官Kathleen Hogan：员工如何充分利用人工智能
Kathleen Hogan Chief People Officer at Microsoft [Photo: courtesy of Microsoft]
微软首席人力官 Kathleen Hogan表示，人工智能对我们工作方式的影响将比个人电脑更大。
AI是我们时代的决定性技术，创造了一个巨大的范式转变，它将改变我们的工作方式，影响力甚至超过了个人电脑的引入。我们曾经有一个大胆的愿景，“每个办公桌上、每个家庭里都有一台电脑”，而今天，我们希望在“每个人的口袋里都放一个副驾驶”。
当然，AI的影响也伴随着挑战。我们必须解决关于工作流失、算法偏见以及组织快速培养技能的真实担忧。但最终，我相信AI的潜力太大，不能采取观望态度。
领导者需要创造正确的环境，让AI获得积极的势头。这将需要准备和有意识的方法，以便这些新的AI工具不仅帮助员工提高生产力，而且帮助他们茁壮成长。我建议关注这三个方面，以更快实现这些好处：培养基于敏捷的文化、重新想象我们的工作方式、投资于更深层次的人类技能。
培养基于敏捷的文化
为了充分利用AI的承诺，团队必须保持敏捷。
即使是那些多年来一直在内部使用AI进行数据分析、预测建模和任务自动化的公司，生成性AI也代表着一个重大转变。通过能够理解人类语言、导航大量文档知识并创造内容，更多职能的员工现在可以使用这些AI工具。
一个基于敏捷的文化还将加速组织建立推动AI价值的更广泛基础和最佳实践的能力。我相信，在AI时代培养这样的文化意味着拥抱适应性领导力，领导者必须愿意深入未知。
重新想象工作方式
20世纪80年代和90年代的机器人自动化进步使制造业生产力翻了一番。这不是仅仅通过给工人提供更高效的工具实现的——公司通过重新思考生产技术和重新设计工作流程，优化人与机器之间的流程，实现了机器人自动化的全部价值。
同样，要充分利用AI采用的价值，领导者需要重新想象工作是如何完成的。这始于将工作分解为更小的任务，以确定AI能做什么，以及或者比人类做得更好。除了自动化一些重复或乏味的工作任务，我们还需要确定AI可以如何协助员工处理更复杂和微妙的任务，如研究、写作和分析。
这个想法是让领导者利用这段时间，不仅是自动化流程，而且是与AI一起重新想象流程，寻找新的工作方式。这将最终帮助人们更聪明地工作，而不是更努力地工作，给他们带来更多的精力，并发现更有意义和更令人满意的工作。
关注人类技能
生成性AI已经被训练了大多数人类语言，所以任何人都可以使用它。但就像任何新技术一样，仅仅给人们新工具而不提供使用它们的技能是不够的。
而且，尽管这似乎与直觉相反，人类技能与技术技能一样重要，以有效使用AI。这包括分析判断力、灵活性、情商、创意评估、智力好奇心、偏见检测和处理能力，以及委派任务的能力。
事实上，我们现在发现，基本的管理技能是发掘AI副驾驶的全部潜力的关键。就像委派给人类员工一样，与副驾驶合作需要能够清晰地沟通，设置背景和参数，定义期望，分析结果，并提供反馈。
一个好的起点是根据学科开发AI技能培训和实践。随着我们从自动驾驶AI转向副驾驶AI，对人们来说，仍然扮演飞行员的角色，用批判性的视角评估他们从AI工具中获得的输出是必要的。这包括验证准确性和评估偏见。最终，飞机的船长有责任成功着陆。
我相信，解锁AI的全部潜力是领导者的责任。AI的创新正在以惊人的速度发生。当我们导航AI对工作场所的影响时，组织领导者必须立即开始培育正确的环境，以确保没有人被遗留在后面。仅仅将AI工具放在员工手中是不够的。当我们培养基于敏捷的文化、重新想象我们的工作方式，以及建立获得AI最佳效果所需的人类技能时，我们可以帮助我们的组织和员工在这个新时代中茁壮成长。
对我来说，能够成为这个令人难以置信的时刻的一部分，既令人兴奋又令人振奋。
英文原文来自：https://www.fastcompany.com/90982077/microsofts-chief-people-officer-heres-how-workers-can-get-the-most-out-of-ai
AI
2023年11月27日
AI
Josh Bersin：Introducing Galileo™, The World’s First AI-Powered Expert Assistant For HRAs many of you know, HR professionals play a vital, complex, and constantly changing role in business. These 30 million professionals hold more than 250 job roles and leverage over 400 skills to help companies with all aspects of management: recruiting, development, leadership, coaching, diversity, pay, benefits, hybrid work, and more. And they must also select and implement a wide array of technologies and tools to help their companies grow.
The Josh Bersin Company, through 25 years of research and interviews with thousands of companies and vendors, has amassed the most trusted library of best-practices, vendor information, benchmarks, case studies, and professional development tools for HR.
Last Spring we embarked on a project to build an “HR Copilot”, consolidating our content into a Generative AI platform. The results were amazing: using Gen AI we were able to build an amazing new experience: users can ask questions, compare vendors, dig into solutions, and generate implementation plans, RFP templates, and more.
Today, in our ongoing effort to help HR professionals drive value for their companies, we’re ready to launch this offering. I’m excited to introduce Galileo™, the world’s first AI-powered expert assistant for HR. (Join the waitlist.)
Every HR Question Answered
Just as Galileo mapped the heavens to explain the universe, our Galileo™ gives HR teams the ability to understand, learn, and seek out best-practices in every area of HR. Powered by Sana’s AI platform, Galileo™ gives users complete access to all of The Josh Bersin Company’s comprehensive research, articles, and tools. And unlike internet-based AI tools, Galileo is free of promotional material, giving you trusted, detailed, verifiable accurate information.
We designed Galileo™ to be the HR professional’s ‘always-on’ resource to learn, ask questions, and develop solutions.
Galileo™ can answer questions on hundreds of topics, provide detailed information on vendors and HR technology, draft RFPs and implementation plans, and give users guidance, case studies, and benchmarks. All of the Josh Bersin Company research is instantly available, with access to in-depth reports, podcasts, articles, and courses. This includes access to our maturity models, frameworks, case studies, and our new definition of terms, The Josh Bersin Company Lexicon™.
Galileo™ will revolutionize the way HR Professionals do their jobs. No longer will you have to guess how to develop a new program or understand a vendor – accurate information is available at your fingertips.
Galileo Is A Learning, Design, And Problem Solving Assistant
Many HR problems are complex. To make problem-solving easy, Galileo includes a library of more than 50 pre-defined “prompts” which help professionals with topics like hiring, onboarding, performance management, training, and multi-disciplinary topics like building a skills taxonomy, implementing pay equity, workforce planning, or designing a capability academy.
We designed these prompts in chains, so as you ask a question, Galileo will take you down a path to learn, explore, and further assist you in your query. (The Galileo Getting Started Guide shows you some of the solutions available.)
Enterprise Ready: Galileo Is Your Company’s Expert Assistant
And there’s more. As you use Galileo, you will want to put your own HR policies and internal information into the system. Thanks to the architecture of Sana, Galileo lets users and teams add your information to the corpus, turning Galileo into your company’s in-house HR and employee assistant. In this private workspace your data and privacy are protected: Galileo is an enterprise grade, secure platform that isolates your data from others, pre-trained by The Josh Bersin Company research.
And our partnership with Sana goes further. Not only does the Sana platform provide scale and speed, it lets us build multiple AI assistants. If you want an expert assistant tailored to specific HR disciplines, like Talent Acquisition, L&D, DEI, or line managers, we can create them without writing code.
“This is just the beginning,” said Josh Bersin, CEO and Founder of The Josh Bersin Company. “This paradigm-shattering offering will change the way companies run their HR organizations and manage their people, enabling any professional to operate like a world-class expert in a short period of time. Galileo is a supportive, developmental assistant, ready to give users detailed answers, real-world examples, and guidance at any time.”
Initially Galileo will be available to our corporate members and later next year we will roll out a version available to members of The Josh Bersin Academy.
We want to thank Sana for their partnership and look forward to evolving Galileo rapidly in the coming months. Anyone interested in experiencing Galileo can sign up for the wait list. We expect general availability in early 2024.
Questions:
What Topics Are Covered by Galileo?
Galileo stores more than 50,000 pages of Josh Bersin Company research, including podcasts, articles, and comprehensive data and analysis on a wide variety of topics. These include talent acquisition, talent management, corporate training, diversity and inclusion, organization design, rewards and recognition, pay and pay equity, performance management, leadership development, global HR operations, hybrid work, culture, change management, and every major area of HR technology.
More than 500 vendors are covered by Galileo and the database is growing and updated every week. Over time Galileo will also include real-time information on new vendor offerings, the labor market, skills and capabilities, and important regulatory changes in HR.
To get just a glimpse of what Galileo can do, review the “Galileo Getting Started Guide.”
Is Galileo Generative AI?
Yes, Galileo is an advanced Generative AI solution that lets users ask questions and prompt the system to compare vendors, list best practices, and even create implementation plans, historical perspectives, and in-depth analysis. This means an HR professional can ask any simple question and Galileo will not only answer the question but give the user follow-on prompts to help them learn more, find examples, or download detailed reports, articles, podcasts, or tools.
What Is The Research and Information Provided?
Over the last three decades The Josh Bersin Company has studied nearly every domain of HR, developing in-depth maturity models, frameworks, benchmarks, and case studies. We have also added all of Josh’s blogs, podcasts, and videos – and we will be adding much more. While Galileo does not include legal and regulatory guidelines (these can be discovered in local jurisdictional systems), it covers every major domain of HR, empowering any HR leader or professional to quickly learn, find examples, and solve a problem.
How Do We Know Galileo Information Is Accurate?
Unlike public domain tools, Galileo is trained exclusively on The Josh Bersin Company’s large corpus of information and research. This means it does not suffer from the “AI drift” problem experienced by internet-sourced systems. In fact the opposite is true: as users query and use the system, it enables them to rate the generated answers and get smarter over time.
How Do I Know That Galileo Is Secure?
Galileo does not train any underlying language models on user input, thereby eliminating the risk of data leakage. Sana, which powers Galileo, is single tenant, ISO 27001 certified, and GDPR compliant. All data is encrypted at rest with AES 256 and in transit with TLS 1.2+. The platform follows data privacy regulations and guidelines to protect each individual user.
Can I Use Galileo To Create My Own HR Assistant?
Yes, Galileo is built on the highly configurable Sana platform, enabling users and teams to add their own content and create new AI assistants. We will offer these private workspace features to corporate clients and then roll them out to individual JBA members later in 2024.
How does Galileo Differ From Other AI Tools?
Many companies are experimenting with Generative AI through public internet tools. Galileo differs from these existing AI tools for the following reasons:
Enterprise Scale, Scope, and Security. Galileo is built on an enterprise scale AI platform capable of loading massive volumes of your own company information. This means you can build on the Josh Bersin Company corpus to safely add your own processes, training, compliance documents, and support material for HR professionals and other users throughout your company.
Depth of expertise. The answers and support you receive from Galileo are based on an extensive library from The Josh Bersin Company, one of the world’s leading advisory companies for corporate learning, talent management, and HR. The Josh Bersin Company has customized Galileo to answer and behave as if it were an expert consultant from their organization.
Source attribution. While other AI chat tools don’t consistently back up their answers, Galileo attributes sources to each answer with specific references and further learning content from The Josh Bersin Company library. And for corporate members, you can download and read the detailed sources.
Privacy. While other assistants may get trained on your data and usage, risking data leakage, Galileo lets you upload your own content without training any underlying large language models on your data.
Workflow support. Beyond answering questions and brainstorming ideas, Galileo helps you solve day-to-day tasks like drafting implementation plans because it can generate content based on both expert HR resources and your organization’s information.
How Does Galileo Get Smarter Over Time?
As we say, Galileo is smart and always getting smarter. It does this through many features.
First, Galileo integrates, tags, transcribes, and indexes all of The Josh Bersin Company’s content on an ongoing basis, making sure the system is always trained on the latest research, findings, and vendor information. Every day we add new information.
Second, answers to questions are generated with retrieval-augmented generation (RAG), identifying the semantically relevant videos, audio, and texts, ranking the sources, and attributing the generated answers to the underlying references. We monitor questions and continuously improve results to provide detail and actionable answers.
Third, we take advantage of user-generated feedback. When users upvote or downvote answers the system learns to provide more accurate answers. The Bersin team works with Sana to improve the detailed answers in commonly asked questions. During the 9-month pilot we already optimized hundreds of questions.
Finally, we have developed “prompt chains” of more than 100 known use-cases in HR and management. Galileo literally prompts you to dive into a problem to learn more, explore vendors, read case studies, and learn best-practices. We will accelerate these solutions over time.
The Josh Bersin Company uses Sana AI’s assistant builder to tailor Galileo’s instructions, specifically adapted to various HR roles and tuned with hundreds of archetypical HR scenarios.
Who Is Sana and What is Sana AI?
Sana is an AI company transforming how organizations learn and access knowledge. Their end-to-end learning platform is trusted by hundreds and thousands of users at leading enterprises like Kry/Livi, Merck, and Svea Solar. Backed by top-tier investors, operators, and founders, they have raised over $80m to date. The company’s headquarters are in Stockholm, Sweden, with offices in London and New York. Galileo is powered by Sana AI, the company’s newest product.
To learn more about Sana, go to https://www.sanalabs.com/galileo.
How Is Galileo Sold and Offered?
Initially Galileo is being offered to Josh Bersin Company Corporate Members, enabling these organizations to empower and support their HR teams in an exciting new way. These individuals can access all the information, download all materials, take courses, and share the tools and information with their teams.
In the coming months there will be a version of Galileo for members of The Josh Bersin Academy. We encourage anyone interested to register on our waitlist so that we can provide updates on availability.
How Do I Get Access To Galileo Now?
Please join our wait list, we are now rolling out Galileo to corporate members and look forward to supporting you.
AI
2023年11月17日
AI
视频：Leading Through Transformation The Future of HR in the AI Era
Leading Through Transformation The Future of HR in the AI Era
Jiajia Chen
Senior Group Product Manager
Nvidia
点击访问：https://www.youtube.com/watch?v=toiy_sBDXHs
以下为演讲稿翻译整理，仅供参考：
引领变革：人工智能时代人力资源的未来
欢迎大家，我很高兴有机会讨论一个自2022年底以来成为焦点的话题。随着chat的广泛成功，许多人开始思考一个问题：我还会有工作吗？对于一些父母来说，这个问题可能会有所不同：我的孩子将来会有工作吗？在深入这个问题之前，让我简单介绍一下自己。我早期的职业生涯涉及多个商业领域，包括人力资源，后来我专注于人工智能产品管理。我拥有几个学位，包括法律学位、MBA学位、经济学科学学位和软件工程学位。我曾在Nidia管理人工智能基础设施产品组合几年。去年晚些时候，我转移到另一个名为Nidia Omniverse的产品组，这是一个数字孪生平台工业元宇宙。我们的企业客户可以使用Omniverse来创建数字孪生工业元宇宙，通过利用模拟和生成性人工智能以及与大型生态系统合作。通过这些经历，我对人工智能和人力资源有了深刻的理解。在这次演讲中，我希望能提供一个框架，帮助大家思考如何在人工智能时代领导转型，如何保持相关性并比人工智能发展得更快。
人工智能并不是一个新概念。让我们快速回顾一下人工智能发展的简史，为今天的对话奠定基础。人工智能领域诞生于1950年代。1950年，艾伦·图灵提出了模仿人类智能的通用机器的概念。1956年，人工智能这一术语被创造出来。在1970年代和1980年代，人工智能最初的乐观预期开始减弱，因为进展没有达到高期望，人工智能研究的资金减少，领域经历了被称为人工智能冬天的时期。在人工智能冬天期间，研究人员专注于发展专家系统，这是基于规则的系统，旨在模仿人类专家在特定领域的知识和决策能力。这种方法在实际应用中取得了一些进展，例如医学诊断和工业自动化。1980年代，人工智能的焦点转向了机器学习和神经网络。机器学习算法允许计算机在没有明确编程的情况下从数据中学习，并做出预测或决策。受人类大脑结构启发的神经网络引起了关注，并被应用于各种任务，包括图像和语音识别。得益于大量数据的可用性和计算能力的进步，人工智能经历了复兴。Nidia的贡献是关键的。
2022年11月推出的ChatGPT标志着人工智能的关键时刻。生成性人工智能正在推动机器创造的边界。人工智能越来越多地融入各种应用和行业，正在金融、医疗保健、网络安全等领域发挥作用，转变行业并创造新的机会。
你们中有多少人尝试过ChatGPT？你们喜欢它的哪些功能？是否用它来草拟电子邮件、创建培训材料，或者提出棘手的问题，试图愚弄chat GPT，证明你的人类智能更高级？人工智能预计将在各个维度对工作场所产生重大变化。
以下是人工智能可能带来的九个变化。
首先，提高生产力：人工智能是否会提高生产力和经济增长？许多人这样预期，但也有很多人告诉你，到目前为止，这种生成性人工智能趋势并没有大幅提高生产力，除了提供一些有趣的玩具。你们中的一些人可能听说过“生产力悖论”，这是1970年代和1980年代在美国发生的现象。我的预测是，人工智能不会发生这种情况。人工智能可以更快地传播，且所需的资本投资更少。这是因为人工智能在短期内的应用主要是软件革命，所需的大部分基础设施，如计算设备、网络和云服务，已经到位。你现在可以通过手机立即使用chat GPT和迅速增长的类似软件。
其次，收入不平等：人工智能是否会带来自动化的奢华时代，还是只会加剧现有的不平等？美国国家经济研究局发布的一份报告称，自1980年以来，美国工资变化的50%到70%可以归因于蓝领工人被自动化取代或降级导致的工资下降。人工智能、机器人技术和新的复杂技术导致财富高度集中。直到最近，受过大学教育的白领专业人士基本上没有受到低教育工人的命运。拥有研究生学位的人看到他们的薪水上涨，而低教育工人的薪水显著下降。这一问题将加剧，低技能的白领工人也将受到影响。
第三，劳动力技能提升和风险转移：随着某些任务的自动化，人工智能需要专注于提升和重新技能化劳动力。员工需要获得新的技能和知识，以适应不断变化的工作要求，并有效地与人工智能系统协作。有关这一主题的研究很多，不同研究的数据也有所不同。彭博社的研究显示，由于人工智能对工作的影响，全球将有超过1.2亿工人在未来三年内需要重新培训。据信，由于人工智能相关部署，中国将有超过5000万工人需要重新培训。美国将需要重新培训1150万人，以适应劳动力市场的需求。巴西、日本和德国的数百万工人也将需要帮助应对人工智能、机器人技术及相关技术带来的变化。根据麦肯锡的一项研究，由于快速自动化的采用，多达3.75亿工人可能需要转换职业类别。
第四，重新定义工作角色：人工智能有潜力重塑工作角色并创造新的角色。一些任务和工作可能会完全自动化，导致某些领域的工作流失。然而，人工智能也为创造涉及管理和协作人工智能系统、分析人工智能生成的内容、开发和维护人工智能技术的新角色创造了机会。例子包括美国政府试图将制造业带回美国。许多人认为，像第二次世界大战后一样，将创造数百万高薪的蓝领工人工作。然而，这最有可能不会发生，因为在美国建造的新工厂几乎不会雇用许多人类工人。一切都将通过机器人或管理系统自动化。
第五，增强决策制定：人工智能系统可以分析大量数据，检测模式，并生成支持决策过程的洞察。这可以使员工和管理者获得更准确、更及时的信息，使各种职能（如运营、市场营销、财务、人力资源）的决策更加明智。2019年哈佛商业评论提出了一个概念，称为人工智能驱动的决策，与数据驱动的决策相比，它允许我们克服作为人类处理器的固有局限性，如低效和认知偏见，因为你可以指派机器来处理大量数据，让我们人类应用判断力、文化价值观和情境来选择决策选项。
第六，人工智能与人类的协作：人工智能技术使得人与智能系统之间的协作成为可能。这种协作可能涉及利用人工智能在数据分析、模式识别和预测方面的优势，而人类则提供批判性思维、创造力、同理心和复杂问题解决技能。如果能够有效地实现人与人工智能系统的协作，可以带来改进的成果和创新。的确，许多公司已经使用人工智能自动化流程，但到目前为止，证据表明，那些旨在取代员工的部署只会带来短期的生产力提升。在一项涉及1500家公司的基本研究中发现，当人类和机器一起工作时，公司取得了最显著的绩效提升。
第七，增强智能：人工智能可以通过补充和增强人类能力来增强人类智能。它可以协助人们执行诸如信息检索、数据分析和问题解决等任务。人工智能支持的虚拟助手和机器人可以为人们提供即时支持和指导，提高他们的效率和效果。
第八，伦理考虑：人工智能在工作场所的整合引发了与隐私、安全、公平、透明度和问责制相关的伦理考虑。组织需要建立伦理框架和指南来确保人工智能系统的合理和可信赖的开发和部署。
第九，监控和评估AI实施。这个变化涉及到持续监控人工智能在工作场所的影响，并从员工那里收集反馈，以识别改进领域。定期的评估和反馈循环将有助于完善人工智能的实施和使用，确保其在增进工作效率、创新和其他方面的应用是有效和恰当的。（以上为AI补充，仅供参考）
目前，我们已经详细讨论了人工智能在工作场所创造的变化，以及人力资源应该如何应对这些变化。
现在，让我分享这张早先在一次HR会议上使用的幻灯片。2016年，我在一个名为“HR新模型”的会议上发表了演讲。现在，让我们看看这个模型。一个典型的组织结构包括首席执行官、人力资源业务伙伴、共享服务和一个运营部门，支持管理者和员工群体。公司是否能用这个模型应对人工智能在工作场所带来的变化？我们是否需要一个不同的模型？在回答这个问题之前，让我们看看应对每种类型变化需要发生什么。在这张幻灯片上，我展示了我简单的颜色编码技术。我简单地将所有类型的能力和技能分类并用不同颜色高亮显示。现在我们可以看到几个主要类别和一些零散项目。让我们稍微深入一些颜色分类的挑战。
首先，以蓝色突出显示的助理挑战和两个工作场所的变化。HR可以评估利用人工智能的技能和能力要求，为员工提供必要的资源，使他们能够理解和利用人工智能技术，以及如何通过人工智能来增强他们的工作。这包括关于人工智能概念、数据分析、自动化工具和人工智能支持决策的培训。HR可以培养持续学习的文化。
其次，以绿色突出显示的变革管理和沟通，在四个不同的工作场所变化中出现。HR可以积极地向员工传达人工智能实施的目的和好处，以提高生产力和效率。HR可以协助经理和员工分析工作并重新设计工作流程，以利用人工智能技术。这涉及识别可以自动化或由人工智能增强的任务和活动，简化工作流程，消除冗余或低价值测试，并确定人类和人工智能如何合作以优化生产力和效率。
第三，以热粉色突出显示的职业发展和内部流动性，在三个不同的工作场所变化中出现。HR可以进行技能评估，以确定组织内现有技能，并确定需要解决的AI相关角色的差距。这包括识别与人工智能技术合作所需的技术技能，如机器学习，以及有效沟通、批判性思维和问题解决所必需的软技能。
最后，以灰蓝色突出显示的伦理指导和治理，在三个不同的工作场所变化中出现。HR可以与法律、合规团队等相关利益相关者协作，为人工智能变革建立治理框架。那些仍以黑色显示的功能在未来几年将看到更多的自动化和置换，投资较少，因为这些能力在人工智能转型中的相关性较低。
为了跟上甚至领导人工智能趋势及其对工作场所的影响，HR可以采取几个积极的步骤。以下是我们可以考虑的一些关键行动：持续学习，HR专业人士可以深入了解人工智能技术、应用和影响；识别人力资源中的人工智能用例，HR可以探索各种可以增强其功能和简化流程的人工智能应用，例如自动化日常行政任务、改进候选人筛选和选拔流程，以及提供个性化的学习和发展机会；评估组织的人工智能准备情况，HR可以评估组织当前的基础设施、技术能力和文化，以确定其采用人工智能的准备情况；通信和透明度，人工智能实施期间的沟通和透明度对于缓解对工作安全的担忧、澄清人工智能采用的好处以及确保员工理解人工智能技术将如何增强而非取代他们的工作至关重要；监控和评估人工智能实施，HR可以持续监控人工智能对工作场所的影响，并从员工那里收集反馈，以识别改进领域。定期的评估和反馈循环将有助于完善人工智能实施。
AI
2023年07月02日
AI
Sana Raises Additional $28M Led by NEA to Build the Universal AI Platform for the EnterpriseSana, a company focused on building a universal AI platform for the enterprise, has secured an additional $28 million in funding, with NEA (New Enterprise Associates) leading the investment round. This infusion of funding will undoubtedly help Sana advance its mission of creating an AI platform that caters specifically to the needs of businesses.
The Swedish-born Sana scaleup becomes one of Europe’s most highly-funded AI companies with $62M in total Series B funding
May 31,2023 Sana, the leading AI-powered learning and knowledge platform, announced today it’s landed another $28m in an opportunistic investment round led by NEA. Workday Ventures also joined the round. With a combined total of $62m in Series B funding, the Swedish-born scaleup is now one of the most highly-funded AI companies.
Sana's mission is to augment human intelligence through artificial intelligence. To that end, the company has built a category-defining product that blends the best of enterprise search, a learning management system, meeting tools, and a knowledge management system into one single platform.
Underpinning this suite of tools is Sana AI, the company's latest release. Sana AI is an omnipresent assistant that can do everything from search across all your company's apps and take actions in response to natural language commands to generating real-time summaries of live meetings and creating entire learning courses from scratch, and writing SQL to query your data. In other words, it's like ChatGPT for your company's knowledge.
By augmenting an organization's ability to capture, organize, and access knowledge at every step through AI, Sana enables any team to move faster and be more productive—from sales and customer support teams to product specialists and software engineers.
"At Sana, we believe every organization's mission depends on the collective intelligence of its employees. That intelligence depends on knowledge, yet most institutional knowledge today is scattered across multiple tools, trapped in people's minds, and lost in verbal conversations. AI is the key to solving this problem at scale. By unlocking knowledge for every employee across any organization, we unlock global progress," said Joel Hellermark, founder and CEO of Sana. "We're thrilled to have the support from NEA and strategic investors like Workday Ventures on this mission."
Sana wasn’t looking for funding when NEA made its proactive offer. The scaleup had a healthy runway having closed a $34m Series B round led by Menlo Ventures last December. One of the reasons for the additional investor interest is commercial performance: Sana has grown its business 3x year over year.
NEA will be represented on Sana's board by CEO Scott Sandell and Managing Director Philip Chopin. Since joining NEA in 1996, Sandell has played a critical role in many industry-transforming businesses, including Robinhood, Salesforce, Tableau Software, and Workday.
"Sana's past track record and current trajectory are exceptional. Thanks to top talent, bold vision, and rare organizational alignment, we believe they've already built a world-class learning and knowledge platform. But what excites us most is where Sana is going next: indexing every form of an organization's functional data through LLMs to become the de-facto AI platform for the enterprise. The use cases for this type of product are endless," said Scott Sandell, CEO at NEA.
In addition to Sana's commercial growth and ambitious team, NEA was impressed by the level of customer advocacy. The platform is used by an impressive client roster of market-leading companies like Merck, Kry/Livi, and Svea Solar—all of whom praise Sana's superior user experience and product velocity.
"Since day one, we've been amazed at Sana's pace of innovation and commitment to addressing customer feedback. The platform is more than a tool—it's become Svea Solar’s home for learning and knowledge. We see the latest iteration of Sana AI as a productivity game-changer, " said Hanna Manberg, CHRO at Svea Solar.
With the additional funding, Sana will continue expanding its product development and commercial teams across Stockholm, London, and New York offices. Sana's headquarters will remain in Stockholm, where founder and CEO Joel Hellermark founded the company aged 19, six years after teaching himself to code in C.
"Joel is an exceptional founder. This Series B extension is a testament to his technical and commercial prowess and visionary leadership. As we enter the new age of artificial intelligence, we believe the Sana team is well positioned to become one of the world's most successful and impactful AI companies," said Philip Chopin, Managing Director at NEA UK.
About Sana
Sana is an AI-powered learning platform that empowers organizations to find, share, and harness the knowledge they need to achieve their missions. Backed by some of the world's leading investors, operators, and founders, Sana has raised more than $85m to date. The company's headquarters are in Stockholm, Sweden, with offices in London and New York. For more information, head to www.sanalabs.com.
About NEA
New Enterprise Associates, Inc. (NEA) is a global venture capital firm focused on helping entrepreneurs build transformational businesses across multiple stages, sectors and geographies. Founded in 1977, NEA has over $25 billion in assets under management, as of March 31, 2023 and invests in technology and healthcare companies at all stages in a company’s lifecycle, from seed stage through IPO. The firm's long track record of investing includes more than 270 portfolio company IPOs and more than 450 mergers and acquisitions. For more information, please visit www.nea.com.
AI
2023年05月31日
AI
Sana Raises $34M Series B to Transform the Way Organizations Learn Through AISana has raised $34 million in a Series B funding round to revolutionize the way organizations learn through AI. This funding round was led by Menlo Ventures, a venture capital firm. Existing investor EQT Ventures also joined the round with several founders and operators. This Series B funding round is a significant milestone for Sana, providing them with the necessary resources to scale their platform, refine their AI capabilities, and further drive innovation in the learning space.
Following 7x year-over-year growth, Menlo Ventures leads funding round to accelerate US expansion
Dec.13,2022 Sana, the leading AI-powered learning platform, announced the close of its $34M Series B led by Menlo Ventures. Existing investor EQT Ventures also joined the round with several founders and operators. Menlo Ventures’ partner JP Sanday joins the board as part of this round. This funding follows a 7x year-over-year increase in Annual Recurring Revenue (ARR).
Sana was founded with the vision of leveraging artificial intelligence to help organizations learn and share knowledge. To that end, Sana built a category-leading learning platform that enables organizations to consolidate their learning and capture, organize, and personalize all their institutional knowledge.
From personalized learning recommendations to an AI writing assistant that automatically generates content, Sana applies the latest breakthroughs in AI to enhance and optimize the entire learning and knowledge-sharing journey.
Sana's AI-powered semantic search empowers employees to get the knowledge they need from anywhere in their organization. The platform connects and indexes tools like Slack, Salesforce, Notion, LinkedIn Learning, and Google Workplace to provide employees with automatically generated answers in natural language. The result: an end-to-end platform that decreases onboarding time, improves sales efficiency, and grows and retains top talent.
"Now a $30 billion industry, the learning and development market has demanded more sophisticated tools. With a world-class product and incredible team, Sana is uniquely positioned to win the market. They offer two vital benefits to the historically underserved L&D category: the scalability and efficiency of artificial intelligence and the compelling experience of a consumer-grade product,” said JP Sanday, Partner at Menlo Ventures.
"The ambitious customers we serve—pioneers like Alan, Svea Solar, Kry/Livi, and Merck—are on a mission to change the world. Sana’s job is to accelerate their efforts by ensuring every employee has access to the right knowledge at the right time. By leveraging the power of AI, Sana can unlock organizational knowledge with unprecedented scale and speed, supercharging the organizations we serve,” said Joel Hellermark, founder and CEO of Sana.
Sana is now the home for knowledge and learning at digital health company Alan—consolidating a myriad of learning and productivity tools. Today, Alan uses Sana to onboard employees, train sales and customer support reps, and develop their leaders.
"Speed, transparency, and personal growth are key to Alan's culture, and Sana was the only provider able to deliver on all three. Since using the platform, we've decreased our ramp time while boosting learner engagement. We think Sana has set a new standard for what organizations expect from a learning platform. Their tech and UX have leapfrogged the industry," said Filip Lam, Head of People Growth at Alan.
With the new funding, Sana will extend its product development and expand its team across Stockholm, London, and New York offices. The headquarters will remain in Stockholm, where founder and CEO Joel Hellermark founded the company aged 19, six years after teaching himself to code in C.
“Joel’s visionary leadership, and his rare combination of being technically skilled and exceptionally ambitious, has enabled him to assemble a world-class team from some of the foremost tech companies. With learning as the foundation of human progress, we believe team Sana has the potential to play an important role in reimagining learning as we know it,” said Sandra Malmberg, Director at EQT Ventures.
"Our ambition is to build an internet-scale Library of Alexandria, where more than a billion people can learn about anything and share everything they know," said Hellermark. "We're thrilled to have the support of Menlo Ventures and previous backers on this mission."
About Sana
Sana is an AI-powered learning platform that empowers organizations to find, share, and harness the knowledge they need to achieve their missions. Backed by some of the world’s leading investors, operators, and founders, Sana has raised $54M to date. The company's headquarters are in Stockholm, Sweden, with offices in London and New York.
About Menlo Ventures
Menlo Ventures is a venture capital firm that strives to have a positive impact on everything we do. That’s why we support businesses including Benchling, Chime, Carta, Poshmark, Uber, and Roku that are reimagining life and work for the better. Over 43 years, we’ve grown a portfolio that includes more than 70 public companies, over 100 mergers and acquisitions, and $5.5 billion under management. We invest at every stage and in every sector, with expertise in Consumer, Enterprise, and Healthcare. From developing market strategies to creating communities, we provide real impact where entrepreneurs need it most. When we’re in, we’re all in. www.menlovc.com
AI
AI
AI
AI
AI
AI
AI
扫一扫
添加客服
