Workday is a leading provider of enterprise cloud applications for human resources, finance, and planning. They recently announced new artificial intelligence (AI) and machine learning (ML) features to help organizations better adapt to the changing world of work. With this step, Workday unveils its interpretation of how to use generative AI to amplify human performance at work with more insights, agility, and innovation. This is obviously relevant for HR professionals.
Take HR Managers themselves. Generative AI offers the potential to automate some of their tasks such as determining the resource needs of projects or managing budgets. But more important than automating tasks is augmenting their job, i.e., by explaining regulations and policies to employees or training others on work procedures. Overall, the role of an HR Manager is not being considered as exposed to generative AI. However, according to the World Economic Forum, the overall function of HR comprises 57% of tasks that can be automated or augmented by the underlying large language models (LLM). So, how do Workday’s announcements impact HR?
What is Generative AI and Why Does It Matter?
Generative AI is a type of AI that can create new content or data based on existing data or rules. For example, generative AI can conduct data analysis, do research, and interpret vast amounts of text. Generative AI can also produce texts, realistic images, sounds, or videos that are not copied from any source, but are generated from scratch. The integration into Workday can help their customers better address some of the key challenges in the world of work.
For example: 
- It can help solve complex problems that require novel solutions, ideas, or designs that humans may not think of or have time to explore. For example, generative AI can help create new services or processes that meet changing employee preferences.
- It can enhance human capabilities and free up time for more strategic work. Generative AI can automate or augment tasks that are tedious, repetitive, or time-consuming, such as data entry, report writing, or scheduling. This can allow HR professionals to focus on more value-added activities, such as decision-making, collaboration, or conversations with employees.
- It can provide personalized and relevant insights and recommendations. Generative AI can analyze large amounts of data and generate customized content or suggestions tailored to each individual’s context. For example, generative AI can help deliver personalized learning content, career guidance, or feedback.
How Does Workday Use Generative AI in Its Products?
Workday says that it embedded AI and ML at the core of its platform, enabling it to leverage its “unrivaled dataset”, its flexible and scalable architecture, and its “responsible AI safeguards”. Workday mixed their announcement of major updates with some minor improvements to existing AI capabilities. Here are the most important talking points about how Workday plans to use generative AI in its products: 
- Workday Extend: A gateway for organizations to build customized applications and solutions with a no-code/low-code toolset or with advanced developer technologies. Developers can access Workday data including skills analysis, sentiment analysis, document intelligence, and forecasting.
- Workday AI Marketplace: A new platform to centralize externally developed apps that can be used within Workday. It’s currently in development with 15 partner companies (Accenture, Amazon, Auditoria, Avalara, Better Up, Hired Score, Intel Agree, Kainos, Kyriba, Paradox, Relish, Sana, Techwolf, Workboard, Vertex). It is supposed to go online in the first half of 2024.
- Manager Insights Hub: A new solution as part of the Workday Human Capital Management (HCM) that gives Managers personalized recommendations to proactively support their team members based on their skills and interests. Recommendations include connections, mentors, or available gigs. The HCM also received a new function with the title Flex Teams that supports Managers in quickly assembling teams.
- Workday Adaptive Planning: An existing solution that has been upgraded with generative AI capabilities and a new interface to streamline workforce planning. Workforce Planners can create new or update existing positions, and change hiring dates or salaries, and their changes will automatically be reflected in headcount planning and budgets.
- Skills Cloud: An existing, updated AI model that creates a common language for skills across industries and roles – and from now on also across geographies because it functions in 16 languages. Skills Cloud can automatically identify skills from various sources, such as resumes, job descriptions, or learning content. Skills Cloud can also generate new skills based on existing ones, such as synonyms, related skills, or skill clusters.
- User Success Platform: Already unveiled in 2022, it will receive new learning paths, improved search, and new integrations.
Generative AI has the peculiarity that the use cases in practice are being determined by the user, as opposed to conventional software where the use cases are predefined by the provider. It is therefore difficult to evaluate the announcements of Workday. It remains to be seen what precisely HR professionals will use them for. But Workday already gave some specific examples.
The first example is the generation of job descriptions. Hiring Managers and Recruiters will be able to create targeted job descriptions based on the skills and location of the role, with the objective to get quicker and attract better candidates. A second example is the creation of personalized knowledge management articles. This feature enables content creators to draft articles that are tailored to their audience, such as talking points for managers or key takeaways from videos, improving the tone, length, and translation of the articles, and overcoming writer’s block. Think about creating help guides for employees, or simple How-To documents for regularly asked questions. Another example mentioned by Workday is the creation of employee growth plans. Managers will be able to quickly create a summary of employees’ strengths and areas of growth, pulling from data such as performance reviews, feedback, goals, skills, and sentiment, making the career check-in process more personalized and effective. HR professionals can also get quicker in elaborating working contracts by automatically comparing them with existing contracts in the system and surfacing discrepancies.
What Are the Benefits and Challenges of Using Generative AI in Workday?
Using generative AI in Workday can bring many benefits to both employers and employees, as well as some challenges that need to be addressed.
It’s quite obvious that it can help improve employee engagement, retention, and productivity. If used properly, generative AI can help employees feel more valued, supported, and motivated by providing them with personalized content, guidance, and opportunities that match their skills, interests, and goals. It can help optimize talent management, learning, and development. And it can help drive business outcomes and innovation. The upsides of Workday’s generative AI features are impressive. But they will only materialize if their generative AI model is trained properly and if it is being used responsibly.
The most important challenge worth mentioning is the potential issue of the existence of bias in the training data. Think about the above-mentioned AI-generated development plans for employees. They are based on text analysis of the training data and employee data. However, we have learned that generative AI models possess a specific worldview depending on the training data used (example). Studies have also shown that AI models fail to understand the nuances of language in performance reviews and the subtle differences in language used by employees themselves. I.e., a non-native English speaker or someone with a specific ethnic background might use different expressions than the majority and will therefore be judged differently and treated differently by the AI when it comes to identifying individual growth paths.
The same applies to text-based sentiment analysis. It is not guaranteed that generative AI can understand the nuances of language to measure sentiments. Workday does not reveal which LLM they are working with and which data is being used to train their AI. However, they prove their experience and consciousness of the problem by recommending using the results of generative AI only as a first draft and then reviewing, editing, and iterating to elaborate a final version. Workday expects there always to be a human in the loop and this seems a reasonable expectation.
Conclusion
Another challenge has nothing to do with Workday as a vendor but with the clients using the generative AI features. Workday has expanded the technological possible for HR but organizations still have to ensure the widespread integration into their processes. Organizations have to determine the individual use cases,
provide relevant data, train professionals on the use of generative AI, and address structural inadequacies that might inhibit seamless collaboration. Navigating these challenges is a multifaceted approach. Organizations that manage to intertwine technological possibilities with human-centric policies will have a large price to reap, creating competitive advantages and progress.
HR is at the center of this process and Workday’s announcements made it easier for HR to understand, use, and then spread the technology responsibly and gainfully in their organization. From this point of view, Workday just gave organizations a major template to amplify human performance at work.