Tag: #FutureofHR

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The Halloween Edition: Scary AI… not what you think

A first of its kind halloween edition on my blog and I thought I theme it a bit that way.

Now, talking about AI there are many things that seem scary to some and others. Mostly such feelings are around how it might impact employment or changes in the workplace, but also how it might impact our public discourse. I am not necessarily disagreeing with some of the fears – as well as the opportunities. Today though I don’t want to write about this, but a different scary AI topic.

ChatGPT – almost one year in

We are arriving soon at the 12 months mark when ChatGPT was released to the public. Last November 30th it was brought to public release and started a hype that since has not really stopped. It was the “App” with the fastest growing user numbers ever with reaching 1 Million users after 5 days and 100 million active users by January 2023. No other App ever managed that. But that wasn’t it. ChatGPT with the help of Microsoft made it quickly into the enterprise market and many of us are experimenting with it or other Gen AI solutions since. Also in the enterprise market this AI revolution has taken offices by storm – may it be IT professionals or functional professionals across all functions – Sales, Marketing, Finance, others – and of course Human Resources. The ideas and applications are universal and exponential. This is also what makes AI so different from the Metaverse or Blockchain. As I already wrote here, Metaverse and Blockchain were interesting new ideas and technologies…in search of a business problem to solve. And they are still in this same position years after they saw the light of day. (Gen) AI came with a set of addressable business problems and has identified many more to solve.

The potential of (Gen) AI

I am sure many of you have experimented with (Gen) AI in the last 12 months as I have and have seen the potential it has and the immediate applicability. We have also seen the flaws and over-hypes. But at its core it was and is a revolutionary technology that transforms the way we do business, the way we do HR. May it be in the Experience space where Gen AI significantly improves the way regular users can interact with HR technologies, even if they only need to use it once or twice a year. AI has solved this issue by “taking users by the hand”. May it be in the skills space where it not only can identify skills you most likely have based on your CV and previous positions, but also has a superior matching quality to find the right job, the right opportunity for you – or helps you with understanding what skills and experiences you need to gain before you have a chance of getting your dream-job. 

Sometimes it felt like (Gen) AI is the solution to almost all issues we have in today’s HR world. Of course that is not true and of course as much as I did, many of you saw some of our test & learn concepts fail or underdeliver against our expectations. But we carried on to identify new ones – especially motivated and cheered by all the Tech companies that had AI technology readily available. And who had not started to get ready. It was a hectic gold-rush for solutions and ideas in the last 12 months – and slowly but surely we wake up to a scary AI reality. A reality that quite frankly we should have seen coming – and for sure some of us saw coming. Question though is if you expected that level of scaring potential.

Scary AI

What am I referring to? – while most of the vendors and partners did let you experiment and even pushed for new ideas for experimentation heavily these last 12 months at either no costs or very low costs, the boomerang now comes back. AI is expensive – especially Gen AI. Each training run for a Large-Language Model (LLM) can cost between $2-$12 Million. It took OpenAI more than $1.4 Billion to get to ChatGPT public release. And the actual usage costs of these models once ready are not cheap either. There is a good reason why NVIDIA’s share price performed +205% over the last year. NVIDIA is the main supplier of the GPU chips necessary to train and run LLMs. But not only NVIDIAs share price performed well – look at Microsoft with an increase of 45%, closing to Apple as being the most valuable company in the world. And of course these investments and expectations are asking for “re-financing” or in other terms, the costs of using (Gen) AI models in regular production applications will cost a scary amount of $$$ in order for these companies to get their investment back and to confirm their promises to the stock market. And guess who should pay that price? – yes, you and me🙂

(Gen) AI is here to stay – there is no doubt about it and there will be some adoption happening. The question is how much and how fast will it grow. We are still in our hype-cycle with (Gen) AI and I believe the costs of (Gen) AI will send us into the trough of disillusionment. How long we stay there depends on two things really

(1) how high the price will be that the (Gen) AI vendors will settle for and if they are willing to defer their returns a bit longer – and yeah, I get it, even the high prices have often not too high margins as costs need to get under control first and

(2) if the price to pay is at least equal, but better lower compared to the additional value or cost efficiency that companies are able to realize. 

We are on the down-turn of the hype-cycle, but how long we will stay there and how deep we will go is an interesting question. I have no doubt that we will reach a rather high plateau of productivity – but when? What do you think?

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Techtember behind us, Techtober in full swing

Hey everyone – as I wrote here, I am very excited about Techtember and Techtober with all of its  conferences and announcements. And I think so far it did not let us down. We had Workday Rising US (I will only visit Rising EMEA later in November – please join me as I will be on stage) as well as SAP SuccessConnect so far.

Workday Rising

Workday Rising had as I expected a full bouquet of AI announcements. They announced the addition of generative AI across its platform and enhanced other, already built-in AI capabilities. They also opened up a Workday AI Marketplace for partners to add solutions and for customers to take advantage of them. As I was already alluding to in my article here, Workday is finally at the table and fully in the AI game. And at the same time Workday stays true to its security and privacy focus in only allowing it to be on your data and within your tenant structure. So you can harness everything without the worry of exposing data. I believe that is the right balance. Openness and inclusiveness of other data sources to read and feed potentially provides better results (which needs to be proven) but it for sure gets you into more difficult conversations around privacy, security and actually IF you can enable it at all. 

These AI additions will bring massive improvements as well as will make sure that Workday stays ahead of the pack of the current competition – and as there is still no new AI-powered contender start-up at present, it might be able to keep its rank for this wave of tech innovations. Some of the functionalities include the ability to generate job descriptions (which already many solutions do – but again, here you can benefit from privacy, security – as well as consistency across the company), compensation related features – and of course the turbo for your developers the “Developer Co-Pilot” that will turn text into code. I am the most excited about their pipeline on improving UI through conversational UI and Generative AI. I believe we all can agree that the current Workday UI/ UX is everything but modern – and so a refreshed look with the infusion of a more conversational approach powered by Generative AI sounds very promising for Employee Experience, for our end-users that today still need to think in HR terms if they want to get anything done. That could be a game-changer. 

SAP SuccessConnect

And of course, SuccessConnect also featured AI big time. Some interesting announcements – but all in line with a strategy we already knew before – in the AI space were made. The less interesting are the “me too” ones like Job Descriptions and personalized learning recommendations. Let’s see how they compare. More exciting though was Joule – SAPs natural-language, generative AI copilot. What is so far though announced is not much more than what e.g. Workday already offers in their Workday everywhere spaces like Slack and Teams, e.g. approvals, finding information, etc. – but what is exciting about it is the concept that we know already from Microsoft – an App-wide Co-pilot that can span across and help (in the best case in the future) with any kind of (t)ask one might have. It is great that it is focused again on the end-user experience. This is where we need to see more focus from these companies and having them all push in that direction will bring great new ideas and concepts that I am looking forward to test. 

Not least, let me talk about the Talent Intelligence Hub. With the focus on a skills based organization this comes at the right time and is all about skills and how to make the most of it, e.g. uniting skills and other data to create a holistic picture of your workforce, making it easy for employees to build their individual skills portfolio, finding the right candidates quickly, or enabling relevant learning and development – in essence an empowerment for managers and employees to take career and progression into their own hands. We need to see how this plays out, but this sounds very exciting.

On both, we must wait and see how presentation and show compare to reality in your own tenants/ implementations. But for sure the announcements have not let me down. It is a big step forward on the road to a democratised HR experience for Managers and Employees. And this is just the beginning – I believe we are still at the top or just past the top of the hype-cycle for AI and the solutions offered seem already very pragmatic and useful – are already addressing real business problems. – and more is still to come.

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Exciting roadmaps and ideas – and wrong turns (a weekend read)

During my recent trip to Silicon Valley, I had the pleasure to meet up with three fascinating companies in the space of enterprise and HR technology. It was my usual visit to reconnect F2F but also understand the direction these companies are going, their roadmaps their strategies. And of course, this year more than ever, it is about understanding how they see (Gen) AI in their products. I met up with Workday, ServiceNow and Microsoft – and they all have (Gen) AI identified to be at the core of their products, but each in their own different ways. That makes it exciting to listen and to understand – and after the in person meetings, I must say that it makes sense to me which direction and adaption they have all taken. All three go different routes, but they have good reasoning behind. If these are correct though and will bring them into the future of HR technology is a question to be answered by the future. As I wrote a few posts back, I believe that we are at a cross-roads when it comes to HR technology. We are at a junction where either the current main players need to reinvent themselves completely or be overtaken by new players. It is a great time to watch and an exciting time to be in the market – however, I hope you are currently not shopping for a new HR core system. It is a difficult time to decide what the future-proof decision will be. I don’t envy you if you are in this position.

Microsoft

But now let’s look at what I have learned. Let me start with Microsoft. They are currently one of the biggest and most active players in the space of (Gen) AI. Their usual surface event this year was more about Gen AI and Co-pilot than anything else (I think they turned to surface devices 40 mins in only). And that speaks to the “all in” that I have also experienced during my visit. Microsoft is bullish about Gen AI and its opportunities. But they have also already learned a lot since the beginning of the year – I believe this is truly contributed by them being in this game early on, but with their open mindset and closeness to the enterprise market. This is what makes the position of Microsoft so interesting. They have not only the technology (OpenAI) but it is paired with an amazing set of enterprise-partnerships and an internal, company-wide growth mindset. You can clearly see how Satya has transformed the thinking and approach of Microsoft and how fundamental this is to their agility in this space.

Now, when I mean they learned, I mean that they are not only focused on Gen AI but at the same time bring in their other strenghts. They know that their customers are worried about data privacy and data security and they know that data, which is at the heart of any successful Gen AI application, is not readily available to be ingested and made use of for Gen AI within companies. And knowing that and being as agile as they are, they made this a product feature as well as new additions to existing products. Data privacy and data security are now at the heart of their enterprise Gen AI applications so that you don’t have to be worried anymore where your data goes and where it might get exposed – or how and where the LLM uses it for their own learning. This is truly a key function in the enterprise market. And in addition, they are deploying additional tools to manage and clean data in your enterprise network and intranet so that it can be used for Gen AI applications. And at the heart of everything lies the MS Graph. In the good and in the bad, because Microsoft is at the heart of the tech infrastructure for most companies, they are in a pole position.

However, of course there is a “but” – and the but is that specifically in the HR space, Microsoft doesn’t really have an idea what use cases make sense or how to apply and integrate Gen AI into the processes and routines. As often in technology: They have a solution and are in need of a problem they can apply it to. Again though, Microsoft being Microsoft, they understand this and are actively engaging with companies to learn and identify the right use cases. It has been great to watch how Microsoft revolutionizes this market with their speed and agility – and I am looking forward to the next few months. Let’s see where we stand in just 6 months from now.

ServiceNow

Let’s then turn to ServiceNow. I had shared my impressions of their K23 conference here, and meeting them in their HQ, my impressions got confirmed. ServiceNow is highly active on Gen AI and this in a truly “platform of platforms” fashion. You can either “bring your own” LLM and connect it to your ServiceNow implementation – or subscribe to their LLM which is more customized and focused on the actual use-cases you might have. And this is also their strength and a differentiator. They have a clear picture of how their customers use their platform and what use cases there are, what use cases bring the most value and how to apply Gen AI to lift that value. This is fascinating to see and amazing how focused and targeted they go after this. I cannot wait till Vancouver is out and the full breadth of their first generation Gen AI application will be available to the wider audience. Being able to test & learn with them on this journey has been a fabulous experience. 

Now, besides Gen AI, of course ServiceNow is further refining their product and unfortunately, what I had already mentioned in my K23 post is becoming more and more true. From being the platform of platforms where you can integrate multiple systems across employee or process journeys while keeping the actual underlying systems in charge, ServiceNow is now heavily focusing on being the only platform, the only interface you see as an end-user. This means that any service is to be integrated and overlayed by ServiceNow and then brought back into the actual application where the data or process is run. I don’t think that this is the right approach and I am not sure who is able to follow such approach outside ServiceNow as a company. You would need 100s of ServiceNow developers to make this happen and to keep it going – and what is the value add? Yes, you will have one coherent UX/ UI across all of your systems for end-users. But what is the price you pay? – you have to pay for all systems anyway, you have to get more support and maintenance staff and, and this is one of my main concerns: You lose flexibility and agility. You will never be able to quickly adapt a new feature from any of your underlying systems because you always have to also update your top ServiceNow layer. 

I believe that you need to reduce the variance of UX/ UIs you expose your end users to – but I also think that in their private lives people can deal with two or three different Apps and interfaces. Of course, these interfaces must be of high quality and straight forward to be used for end-users. But the difference of approach is that if these interfaces are not where you need them to be, you attack the root-cause and work with the system partner to fix this and improve the UX/ UI. I do not believe in plasters (vs. fixing the root-cause) and placing ServiceNow as the only end-user interface on top of your other applications is a plaster and nothing else.

This is however, not where my concerns with ServiceNow end. As some of you have probably seen, ServiceNow is also entering new territory. They are offering “core” Talent territory solutions in the spaces of Learning, Performance Management, and Skills – and I have not heard any voice saying that they will stop at that. Now, if you want to have a one-platform solution only, you might soon be able to use ServiceNow for most of it in the Talent space – but where I am concerned is that this strategic direction will bring them into difficulties with the likes of SAP/ SuccessFactors or Workday and others. This will ultimately take the direction of a rivalry vs. a partnership between these companies – and the impact of this will be felt by us Experience and HR Tech leaders when suddenly Successfactors or Workday are no longer playing nice with ServiceNow and therefore your integrations deteriorate or require more customization. I understand that ServiceNow is looking to grow in new directions, but as a market observer as well as practitioner I am not confident that this is any good for their main customers.

Workday

And last but not least Workday. I have been quite critical about them and their AI journey recently and was looking forward to a more in-depth conversation in person at their HQ. I was not let down. We spent a good time with Dave Sohigian, Workday CTO, to talk about AI and how Workday thinks about it. I must say that I am encouraged after what I have learned that Workday has understood what is at stake and that they will accelerate in this space with a balanced strategy. I am sure that they will share more during their Workday rising conferences and I will wait to hear from them there. But in essence they are similarly looking into an open eco-system of OpenSource or best of breed LLMs they can use and apply them onto their data. This makes sense from the perspective that it is a controlled application and the data that is used is clean and structured – because it is the data of all Workday customers that opted into sharing as part of the innovation agreement. On the other hand, it is of course a limited set of data even for the size we talk about including 80% of Workday customers. Competitors are more open and are using data sources that might be less structured and more contaminated with bad data. So the question is – and I don’t yet know the answer but am looking forward to it being answered – what is better: Tons of data of good and questionable quality or great, clean data but less. What is better for the performance of these specific AI applications.

And with that, let me close today’s post and thoughts. I am looking forward to the announcements that will come our way from all the Techtember and Techtober conferences and see where the industry is going. 

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HR infused AI-use-cases

The world of AI is still fairly new – especially when it comes to generative AI and to its applications in the business or even HR context. Since I posted my last piece, also Josh Bersin has published a Whitepaper on AI in HR which is worth a read. Interesting assessment as well as explanation of what AI is and why it is different from previous ways of working with data and analytics.

With this tone and direction, meaning that this is my personal view and definitely not a complete list, let me share my view on the most interesting and impactful use-cases I can see currently in the HR space. Some of them are already in use or in test – some of them are currently still in the ideation stage.  Maybe not all will be a success in the end, but I believe that all are worth exploring. To structure, I am turning towards the outcome and experience lens as I wrote in my last post: Which use case provides a good outcome for whom with what kind of experience? How can AI transform the way we operate today for which persona? 

AI for your HR Services

Let’s start with the HR Operations persona. Usually you have a fantastic foundation to utilize AI in that space. By now many companies have standardized processes and tools, standardized and documented procedures and knowledge. This is great because this is what AI will need and can utilize to power-charge this persona. For this persona there are mainly two aspects to focus on: efficiency and correctness. 

The regular day-to-day activities in HR Services are focused around getting transactions/ getting cases done as well as answering employee questions or requests. Both is highly structured and repetitive – and based on clear guidelines. This is actually an easy task for (Gen) AI. And the main use-cases I see here are (1) Query handling and (2) transaction processing.

The holy grail of Shared Services is to reduce or completely avoid employee queries that require a human to intervene. In the past we have tried to tackle this problem with a great knowledge base and a simple user interface for employees to “self-serve” their answer. To improve, we have focused on employee centricity, clear and simple knowledge articles as well as a consumer grade UI/ UX. This has brought us far – but there are still sufficient cases where either an employee doesn’t want to search for him-/herself or just can’t find what they need. In such cases, employees approached the Service Desk . We have tried to mitigate that and reduce this number of contacts further by utilizing chatbots which – let’s be honest here – mostly annoyed our employees more than that they helped. Generative AI is the deal-maker here. The capability of having a true 2-way interaction and conversation with the fact that the required answer is for sure somewhere in you knowledge base will make THE difference here. And once successfully implemented, it will open up a whole new way of interacting with employees.

But this is not where I see it stopping. Looking further up the value chain of HR Services, we arrive at the transaction layer, which has been reduced in the past significantly via self-services. But (a) not everything can be done as self-service and (b) not all self-services are zero-touch and last but not least (c) not every employee is actually making use of self-services. The introduction of (Gen) AI in this space can help deliver significant value and unlock the true potential of our Services employees. (Gen) AI can further automate transaction delivery than RPA was able to do so far. Having a native AI engine in our transactional system can take the burden of mostly repetitive, non-value-added work away from your Services employees and free them up for true value adding tasks and human employee interactions. This could even mean that we turn back the trend from being a less human-to-human connected service delivery to a more human-to-human connected service delivery as suddenly there is capacity for such interaction.

(Gen) AI in HR Services has the potential to completely revolutionise the Shared Services model. Many past “not possibles” are now thinkable – and with it you can restart shaping your HR Services structure, set-up and WoW from the ground up. In fact, I suggest you start completely fresh and not from any current set-up, structure or reality. The same that is true for (HR) Technology is true for Shared Services Organization – you can bold on AI to your existing Services and improve them slightly as well as gain efficiency or you can model a new way of HR Service Delivery based on and with AI at its core. The latter will be more difficult, but will also bring more value.

AI for Business Partnering

This is one of my favourite topics as I see so much value in getting this right. In many companies I have seen, HR Business Partnering had and has significant room for improvement. Often, it is not even clear what it truly means – and then there is a misperception between expectations on the stakeholder or client side and on the HR side. And this is before companies have identified HR Business Partners or more personal HR support as too expensive and a regular ground for savings. 

AI has the chance to roll the wheel back while jumping forward multiple steps. 

Let me explain my thinking. I strongly believe that Business Partnering is important and needed while at the same time I am a strong supporter and believer that team and employee accountability sits with the Line Manager (which is why I love to call that role People Manager). People Managers need to do a great job in People Management to make sure their teams are performing as best as possible and we have least voluntary attrition as possible while still ensuring growth opportunities. In many companies despite the fact that People Managers need to lead, guide, develop and overall manage their team, they have further accountabilities. And often these further accountabilities are deemed more important and their “true job” than being a People Manager to their teams. I think we all in HR had this conversation and discussion point more than once. If anyone has found a settling answer that makes all parties happy, please let me know. 

(Gen) AI now can make a big difference here. I see two main solution vectors. Very closely interrelated with the use case for HR Services, let’s have a look at transactional activities. 

AI as advanced admin or foundational HR support for Managers

We ask People Managers to initiate any team related change/ transaction via self-service before it is then handled by HR (either by a person or via automation). This often takes time away from the People Manager without adding much value – I think we can agree on that. Now, with the help of an AI powered business partner co-pilot, such transactions can be initiated faster and in plain language vs. the need to fill out a form which can be complex if you do it only once or twice a year. And (and I will elaborate more on this in one of my next posts) even more than that it can help bridge the gap that we have today between what a People Manager wants to do (e.g. I have a maternity leaver coming back and want to place her into a new position as well as make sure the salary is properly adjusted) and the way our beloved HR systems need it. People Managers don’t think in business processes or HR workflows or transactions. They think about their employees as a whole and want to achieve ONE outcome (e.g. the leaver being back at work with correct compensation). Today we ask People Managers to submit the wanted outcome in multiple transactions – tomorrow, a Gen AI powered business partnering co-pilot can analyse the wanted outcome in plain language and break it down into transactions the HR systems need to achieve that wanted outcome. This is amazing!

AI as foundational people coach

But this is not where I see the Gen AI Business Partner stopping. It could be a proactive co-pilot that helps and coaches the People Manager daily through the “HR” tasks of being a People Manager. It has full access to Team and individual data if it is based out of your HR system, and you could add calendars, emails and whatever else you have available to provide a wider understanding of what work the People Manager and its team are actually doing. And with that data it can nudge, propose, coach certain reviews, activities or even performance evaluations. It can provide these nudges or suggestions timely and then also help “getting it done”. Let’s go back to my above example of the return from maternity leave and let’s say that the People Manager did not review the salary. The AI would do that in the background anyway and compare with the rest of the team, similar positions or jobs as well as experience and would propose that the People Manager initiates a pay increase – and how much that should be. This will not only be a great experience for the People Manager, but will also help significantly keeping your organization compliant – in this case on pay. 

The abilities and use-cases for the People Manager are significant and it all could address multiple issues we face today: (a) human business partners are expensive and so not every Line Leader will have one, (b) Line Leaders feel overwhelmed by the level of self-service that is expected from them, (c) not all line leaders are good People Managers and need coaching on this. The value add of (Gen) AI are amazing and could not only improve your efficiency, but could lead to better team outcomes with intelligent coaching.

AI for HR

I have already above entered HR territory when it comes to coaching as well as wider Talent & Performance Management. And there is so much more. I will explore this in more detail in my next post. I think this was already a lot of food for thought. And as I said, some of the above is already in test & learn – some is a great idea – some but not all of above will make it into real environments and add value. I don‘t know what this will be, but if you don‘t experiment now, you will never know.

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AI utilisation considerations – what to think through

In my last post I provided my reasoning of why “AI or NOT AI” is not the question you should ask. It is a must that you are working actively on PoCs in the AI space and it is a must that you work closely with your HR Tech vendors to push them but also to leverage what they have to offer early on. In the end, even with AI the simplicity rules for your tech stack that I have described here should stay true. This means that you should try to avoid too many different technologies and vendors in your environment. Two many different technologies on the front end mean that your employees will get confused what to use for what and how to use it. As I have iterated a few times, every technology works different, looks different and therefore asks your employees to learn it. Less is more here. But also as little “big” changes as possible. Make sure you slowly implement changes if you can so that your employees continue being used to your landscape, the UX/UI and know their ways around. You don’t want them to lose time or get frustrated when something that they need suddenly looks, feels different or is found at a different spot. Of course, every now and then you have to bring UX/UI advancements, but make them count then.

And in your back-end, the same rules apply. The more and the more different technologies you push into your back-end tech stack, the more complications you have to manage it, to keep things going, which in turn leads to higher maintenance effort and slower upgradability. Two things you don’t want: Wasting time, effort, resources and money to just keep the status quo running. 

So, also in AI consider what your current vendors have to offer first or work with them to get in return an integrated (Gen) AI experience. This is far more preferable and impactful than integrating another tool, another way of operating. But also, (Gen) AI is still new and in the hype-cycle. So, continue to watch the landscape – new vendors, current vendors and try things out. Don’t just wait until the market has settled – you will be too late then. And if only half of the promises of AI hold true, you cannot afford missing out on the efficiency promises as well as on the talent promises. Your competitors won’t wait and will have an advanced state and knowledge to make even better use.

So, don’t wait. Invest in PoCs with your current vendors, new vendors and available toolsets. But watch out, many companies come out with ideas and tools to be used in that space. And not all of these are actually properly backed by security and privacy. We have already seen that some enterprises do not allow usage of such tools anymore – and that is a good thing. At the heart of these models is continuous, life-long learning embedded, and so they absorb all content you provide to it. And if this is any confidential information or even PII, these are in the wilderness quickly and you cannot control it anymore. This is a worst case scenario that some of the first adopters of AI technology face now. 

Similar caution has to be exercised when you either develop your own solution or go with current OOTB solutions. Make sure your environment is secure and no information is leaving it or is used for generic AI training – and if, that all that this AI is actually learning, stays within your organization only. You actually want continuous learning of your AI to get smarter – you just want it to be smart with your data only within your (virtual) 4 walls. Securing your AI environment is the first key step – regardless which way you follow. And of course be careful with PII in general. 

Now, looking at AI, there are many interesting use-cases. Maybe not all will be a success in the end, but I believe that all are worth exploring. To structure, I am turning towards the outcome and experience lens: Which use-case provides a good outcome for whom with what kind of experience? How can AI transform the way we operate today for which persona? – in my next post I will go into detail for the personae of HR Services, Business Partner as well as the regular Employee and People Manager. For each of them, (Gen) AI has something to offer – actually a lot. It is so exciting how work will change, how our whole function will change. But more next time. – do you do any AI PoCs? Let me know in the comments.

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Generative AI – finally someone that understood the task

As I was on my way from the Knowledge23 conference in Las Vegas and going through my notes, pictures, and videos I took, I was still pumped with excitement. Of course ServiceNow has not forgotten how to have an awesome conference, but what really excites me most is that ServiceNow has understood the task of the day. And now, a week afterwards and with some distance, I am still very confident that ServiceNow is on the right path into the AI future.

Generative AI…

In so far no other presentation or announcement have I seen so clearly the commitment to (secure and private) Generative AI than during the days with ServiceNow. Of course, as the others, ServiceNow is stating that they have invested and provided ML and AI solutions in the past – BUT, and that is truly the trick here, they admitted that since GPT 3 the scenery and brief has changed. And they have taken on that challenge. They have an ambitious but thought through plan and roadmap how and where to utilize Generative AI and how it makes the business case for the core persona’s that interact with ServiceNow. They have solutions for developers, for admins, for agents and for employees – and the great thing is that these all work hand in hand. 

…easy to use

But they not only have a clear vision and roadmap on how to utilize Generative AI and multiple different ways on how you can make use of it (e.g. bring your own LLM or take what ServiceNow provides), they also have thought through how to serve it to the different personas in a way that is easy to absorb and provides clarity as well as assurance that nothing hidden is happening. They are looking into a new UI/ UX on how to interact, absorb and immerse into AI resolution of whatever you want to get done – may it be an answer to your HR question or developing a new case form. I really like how they are evolving the interface on their main portal solutions and bring together the Assistant and Search functionality into ONE. None of this is released yet, but coming very soon – so stay tuned.

Of course there is also bad news…

But also at ServiceNow not everything is fantastic. Not sure if you already saw the announcement around skills management and performance management…ServiceNow is moving into HCM territory. And my question is WHY. For years we had a (mostly) peaceful co-existence of HCM platforms or Talent platforms and ServiceNow as “Platform of Platforms”. And I am sure many of you are using ServiceNow as exactly that: A Platform that connects across the rest of technology you have that provides a seamless and attractive experience to employees as complexity reducer. That was and is their strength if you ask me. And of course, it was already in the past not always easy to make all different players be nice to each other – but now that ServiceNow is aggressively pushing into Core HCM territory, I wonder where we as customers of both ServiceNow and SuccessFactors, Oracle, Workday or others will end up. We are the ones that need to make sure they function seamless and integrate nicely – and now they go into competition. I am not sure what I should think about it and I am not sure how this will play out, but I am concerned.

The Leadership Team at ServiceNow is smart and Bill has led SAP for some time, so understands the HCM market very well – but I am not sure what their thinking here is or was. I am not convinced that this will add value to us as customers. We shall see…

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AI infused HR Copilot

In my last post I was referencing that the real and actual business case for AI is not in Search but in the enterprise market. I continue to believe in that and with all announcements that you can see from Microsoft or Google, this becomes more and more apparent. Interestingly though, it seems as if the current enterprise market players are not seeing it or understanding it. Yes, by now (finally) some of them are at least showing some progress in their blogs, but when you read these from Workday or SuccessFactors you see that they still don’t understand the size and impact of the AI wave that is coming their way. 

AI will transform the way we do HR. I do not believe that there is any way this change and impact can be overestimated. Of course, you have the small AI applications as the current enterprise HR software companies bring to the market in the skills, talent or even recruiting space (see also Beamery). But these are not (different than promised) at the core of the solution, at the hart of the platform. These are edge cases where AI provides a very specific job. What I am talking about is an AI first HR platform that actually brings it all together and acts as a connected bridge.

HR Admin powered by AI

Let’s dive into the boring work of HR Administration. Not many people like it but it is still the foundation that not only HR is built on but the whole company. Show me any other enterprise software that is so interconnected and whose data is used to run more business processes than your HR Core Master Data and Organizational Data. You can’t find any. And so, the foundational HR Admin work continues to be at the center and heart of everything we do in HR. But it is still today very transactional and manual. Of course, there have been many improvements over the years and also automation is continuing to help, but a real revolution will only happen with AI. What if instead of a Shared Service Center AI will take care of all transactions. The complexity of 85%+ of all transactions is low to medium and the decision trees are very much rule based to a certain extend. Build an HCM software with AI at its true core and you can eliminate more than 90% of the admin work because AI will do it for you – seamless and in the background. Position movements, promotions, compensation changes, whatever there is, AI can operate it independently. And it won’t only do it for you if you trigger it, e.g. someone starts a promotion and the admin steps to follow are then taken on by the AI – no, with the vast knowledge of the organization, its rules and how it functions, AI can and will provide proactive guidance.

Your personalised AI HR Concierge

In the recent years we have more and more transformed the HR Business Partner role (and yes, I am on purpose talking about the role as I still see too many so-called Business Partners that continue to do HR Manager work) into a strategic, workforce guidance and consultative space. This role will continue to exist and add more and more value in our complex world – but also AI supported. However, the less strategic work can and will be completely transferred into AI. And with that, we are actually bringing back something that Managers and Employees mis, what we took from them: personalized services. AI can provide a personalized HR Concierge service to every employee in the company, including Managers. It will know you and your function and your career path and the typical company career paths, required skills, your existing skills, the gap, ways to close this gap, etc. – the knowledge is almost endless and with that knowledge, the HR Concierge can help any employee to find the right career path, the right training but also can help in many other situation – may it be a benefits question or may it be explaining your pay-slip. And it will free up human colleagues to be available for the more sensitive aspects of HR which will of course continue to exist. Our function will never be without human interaction!

And for Managers, the support will even be bigger. Managers will have an AI HR Manager that can help them manage the HR side of their team, make them aware of opportunities and gaps in their teams, make them aware of risks and issues, as well as help them get their teams into the future based on company strategy and objectives set. AI at the center of a reimagined HCM system will be so powerful and transformative that the current HCM systems and its capabilities will look like a calculator compared to 2023 Excel with Copilot – because this is what it will be, your HR Copilot.

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The AI Battle – we are getting it wrong

My recent posts were all about next level or future HR – with AI mindset first, opportunities and wrong turns we could take in the coming probably more days than years – seeing the announcements from OpenAI, Google and Microsoft (and others) just this recent week makes you think that the AI wave is coming even quicker than we thought. It is amazing what is possible already, but we also must be sure to take off any pink glasses we might wear. We are very much still in the early days and AI is not the solution for everything. Despite the fact that every company and every VC is now heavily running towards it and pushing it (Goodbye NFTs and Metaverse). This will end up in many many failed start-ups (if they actually make it after SVBs failure – the question is how they will be able to get funding – but this is a different story). We are at the beginning of the AI hype-cycle – still an important one, a historic moment in time, like when Steve Jobs showed off the first iPhone (which did not take off then, but it took some time and the App store).

Do we get it wrong?

When talking about AI, Google, Microsoft and OpenAI it is often talked about a war around search and the end-user internet. Even Satya Nadella has shared that view in a by now very famous and for sure historic interview with Nilay from the Verge (watch the video) “I want people to know that we made them (Google) dance”. And yes, of course search is one of the biggest markets out there where just a 1% share increase means many Millions of $s. But I would argue that we get that wrong – not that this is a fight and that this might lead to more search market competitiveness, but that this is the interesting fight to watch.

What is interesting is that it very much looks like Google and mostly Microsoft will win not only the AI, but the Business AI war. Both are already actively pushing applications into the enterprise world, into their enterprise solutions. This is the best approach to make money and get quick traction – and it could be a journey to overthrow the current leaders in HR enterprise technology. I mean, look at Oracle’s webpage, look at SuccessFactors or ServiceNow – they all have one thing in common: Absence of AI mentions on their homepages. Only Workday is actively marketing this area. They have AI on their webpage and during their Innovation Summit they announced that they invest in AI and have a roadmap (read more here from Josh).  – but also let’s be clear, they all have missed the first boat and now need to quickly catch up or become obsolete. And the problem is that even if they think AI, they don’t think “AI first mindset“. They try to “upgrade” their solutions with a little bit of AI here and there. This will not lead to a winning position (happy to talk to you if you believe I got this wrong), or as Oren Harari famously said “The electric light did not come from the continuous improvement of candles”. If at Google there was panic and chaos when Microsoft announced Bing with ChatGPT, I do hope that there is hell at Workday, SAP, Oracle and ServiceNow seeing how Microsoft and Google push AI into the enterprise market. Interestingly I haven’t seen or heard anything like that, which is telling. 

The new wave of HCM

Their products today are “digital first” at best – some of them have last upgraded their UX/UI years ago and don’t even look & feel current anymore. And looking under the hood, they continue to be dumb transaction focused almost ancient machines despite all the marketing nonsense. They need to reimagine themselves quickly – or acquire AI knowledge and capability to overhaul their core. This is now an unexpected point in time where the latest Gartner Magic Quadrant from 2022 is more than outdated. A new playing field has been established with new rules. Who will win? – and to have a chance to win, who will actually show up on the playing field? Stop trying to fix your current product, start from scratch is your only chance.

Google and Microsoft (and other AI players) are there and Microsoft has more than enough enterprise experience and HR technology experience to get into a new leading position if they wanted to. The time is up for what was great in 2022 – it is a new era that is starting and everything has to be rethought with an AI mindset first – and, and it would not be this post from me if I would not mention it, EX first. These are the two new leading aspirations. Build a new system that is thought of AI first with an EX goal. This is a massive task of course and it won’t happen quickly. But we might see a new era of HR systems. – remember, it took SuccessFactors and Workday years from existence to full functional scope to eradicate SAP HCM. And it will take another decade before the new winner is at the top – but the foundation for this winner is laid out now, today. 

I think it is the most exciting times now to be in HR and especially HR Technology and Experience. It is so wild to watch but also be part of it. Let’s let the game begin! – and if you are building one of the new exciting AI first HR systems I would love to talk to you!

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Digital First mindset is so yesterday…

I haven’t talked about my dream for a long time, but it is still in my head and it is my long-term goal that I want to achieve from an Employee Experience perspective. I haven’t talked about it because it got lost a bit in the day-to-day work stuff as well as day-to-day research activities. But I was recently reminded of it when I had a great conversation with Microsoft.

What is a great Employee Experience about

But let me start with this: What is a great Employee Experience about? – as I had shared in the past, for me the best experience is one that seamlessly works, without effort, without need to learn or remember anything. It should be ambient. With everything we have done so far, this goal was not in reach. We worked on creating much better experiences than we had in the past for our processes and systems – but it was everything but ambient. You had to log into a system, you had to find the right service, you had to reach out to get information – may it be around policies or processes or may it be around your team. Yes, we made it more effortless and easier to navigate – but it still required an effort by you.

Ambient HR

Ambient HR is the opposite. It sits quietly in the background, it doesn’t bother you, it doesn’t require anything from you – but when you need it it is there and will support your requirements. And if it believes you should need it, it will reach out to you. Wouldn’t this be great? – you log into your work on a Monday morning and you are directly contacted with a message along the lines of “hey, your team member Carol did a fantastic job in the Myth project. Do you want to recognise her for this? – you could send a message or even do a monetary award. Please let me know” – I would love this support. You have your own People support at your fingertips. But where would this come from? – well, the information for this are already there. In your current systems. Carol did finish that project and had updated her Objectives with feedback from her project manager and the way your company rewards great work is via monetary awards. It just needed to get joined up and presented to you – and from there you can actually just indicate that you want to initiate a monetary award…

This is my dream, and I wanted to achieve it till 2030 – but maybe now it is closer than I thought?

The AI first mindset

And this is when I had a chance to chat with Microsoft. Of course, as many of you these days, I reached out to Microsoft to talk about OpenAI, ChatGPT and how we could integrate it into our current tech stack and improve the experience. And there are, as you know, plenty of ideas on how you can utilise AI to improve the experience and automate chats and processes and more.

But, and this is a big one – but you can also completely reimagine the Experience. It is the same like with “Digital first”: Don’t try to digitise your analog processes, reimagine them digital first. – and therefore the direction should be: Don’t use AI to make your current processes smarter, reimagine everything with an AI first mindset. This is for sure something we all have to learn first. It was not easy to learn “digital first mindset” and it was just “yesterday” when we believed we got there. And now it is the next one and it is even bigger “an AI first mindset” in recreating experiences, in transforming the way work is done. – Digital first is so yesterday….

The new Experience with AI

It is another, even bigger revolution on the horizon, actually not on the horizon but already close to our doorstep. Of course, we won’t be there tomorrow, but probably the day after tomorrow. And with that let me get back to my conversation with Microsoft. Of course, we have talked about how to integrate AI into the current processes and systems and how such a generative AI can be an exponentially better ChatBot than what we have today. But then we went off and into the AI first mindset. What if we can reimagine everything from that perspective, what if we could have as the only interface an employee and people manager needs to have a small bubble at the bottom right of your screen (or anywhere you can imagine). And what if this is not just a bot to answer questions (more or less well) or a bot to bring you into the actual software interface? What if this is the only interface? And it is reaching out to you as much as you are reaching to it. It keeps track of your actions, requests and HR needs and keeps you posted on this, as well as fulfils any need you wanted? – we would go “back in time” to a white gloved HR service, just that it is not by a human – and that it is always 100% customised to you as it knows your data, your team and your direction.

I agree, it is also a bit scary and the critical guardrails need to be defined so that it is a support and not more than that. It is already now more than a dream and we need to make it happen now – forget about digital first mindset, it is AI first mindset as of yesterday!

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Can you remind me, which year do we have?

Let me be straight forward at the beginning: I continue to be very excited about AI and especially about the race we are currently seeing around conversational AI between Microsoft/ OpenAI and Google (and others). This will truly revolutionise the way we operate and interact with technology. As I have written here, I immediately see two very interesting and beneficial use cases that I am actively pursuing (and there are many more).

But the more I dive into AI, the more I am wondering which year we have and if we are going back to “the good old days” of Taylorism and Fordism? – just a short recap “[…] the task of factory management was to determine the best way for the worker to do the job, to provide the proper tools and training, and to provide incentives for good performance.” Taylorism or Scientific Management did see the employee as a work tool to be optimised, as an anonymous body, not an individual – and was often criticised for that (afterwards). And I believe that this criticism was and is right. What we need and what we should strive for at work are individuals, is diversity – not only of backgrounds, gender, race, but also diversity of thinking and working and leading.

Now, when I then read about additional “interesting” applications of AI as a coach to employees, or even further, see the application of it – may it be in MS Teams or in Apps like Humu – or read articles like this, I am left speechless, truly. It seems to come down to a blind believe that technology and AI will make us all better at work because it can analyse “us” and propose “better” behaviours, more effective and efficient behaviours. Am I the only one who is shocked and scared?

We basically propose to go back more than hundred years to improve workers behaviours and outputs – with the only difference that a hundred years ago we at least had the decency to have humans improve humans – where as now we leave this to machines. I see where this is better?! I am not sure I agree with the ethics around this. Just imagine how far this could be driven? If you mix this with Neuro-Science you very quickly go from “suggestions to improve your work” to “manipulation to increase your output”. And because it all comes somehow through the back-door as “new and shiny” AI, we don’t recognise that this brings us back to dark times that we all believed we had left behind. Of course it is just one article, but read this one here and enjoy the sentence of “Enable technology to work on the worker (and the team)” – I am still speechless. Am I the only one?

AI is the new breakthrough technology, there is no doubt about that. It will radically change the way we work, we interact with technology, we search for answers, we analyse data and we hypothesize. A new, not yet elegant, but very powerful tool is been given to us and we need to see how we use it best, where and which use-cases have the best payback and how we bring it from investment to return (of investment). But with any tool, with any new approach, we must be careful and not forget that there is always a downside. We must invest as much research in the downside as in the upside and we must be careful to not use AI in any use case there is, but only where also from an ethical perspective, it is the right thing to do (not to mention that in any case it needs to be cost efficient – don’t forget how much power and energy-consumption these large language models still require). 

And to close my post for this week, let me ask you to go out there and test & learn with AI and don’t forget to jump on this train as it is a radical and fundamental enabler for so much of our work – but to also make sure you have your ethics straight and your ideas and solutions maybe independently reviewed. AI is truly the future also of HR and Employee Experience.