HR Digital Transformation and the Rise of AI in the Corporate World

HR Digital Transformation and the Rise of AI in the Corporate World

HR Digital Transformation and the Rise of AI in the Corporate World

The integration of artificial intelligence (AI) into human resources (HR) practices is enhancing organizations.

AI not only helps to shortlist and recruit the best candidates but also tracks their evolution and performance in the workplace. AI has applications across numerous industries. AI’s global market share is expected to reach $59 million by 2025. This statistic is a sign that all industries, including recruitment, must embrace AI to stay future-proof. Changing the hiring process by using AI in HR will lead to an overall improved work process.

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The transformation of human resources [1] is gaining pace. In this article, we will mainly focus on five of key areas. The digital transformation of HR is bringing the professions into a world that is both more attentive and more digital. It is having a direct impact on job descriptions for all HR management roles. Modern HR departments aim to be more responsive, mobile and productive in order to attract and retain as much talent as possible. We believe that artificial intelligence can make a significant contribution to helping HR departments adapt. It will at least give them a head start and a comparative advantage, which they will then have to work to continuously maintain. 

Five major changes have marked the new normal era characterised by Covid-19, the cost of living crisis and the war in Ukraine. There may be others, but these five sociological changes seem to be shaping a new world, that of the HR management professions of tomorrow. This article is based on interviews conducted with consultants working in HR departments and attempts to summarise the points most frequently raised.

Firstly (1), the need to maintain a high level of attractiveness to capture the attention of young people. The feeling is that today’s young people aspire to greater ethics, even if this means earning less. The ethical values of the company hoping to attract young people and the career paths offered must be tailored. Before, the focus was on remuneration and training. Now, young people want to be supported and also benefit from a work-life balance. They also visit the company website and look at the indicators regarding diversity and therefore the employer, analysing all these indexes. The nature of onboarding has also changed in line with what we call “boomerang” employees. Young talents acquire benchmarked knowledge of companies and are no longer “loyal” as before. They no longer want to wait a year to make up their mind and commit. It is therefore important to offer career paths and several careers. Sometimes, the very idea that a company is open to “slash careers” is seen as something positive, i.e. one person with several activities. We also need to pay attention to departures and processes in line with new HR paradigms; these new attitudes driving employers, companies and employees will foster more attentiveness and simplicity and, in the end, greater agility. There is a continuous need for feedback in this respect. It is therefore a matter of corporate culture: feedback culture. Using AI solutions such as Neobrain, trouvetavoie or Great Place to Work, or using it for new forms of animation with video can, therefore, be a facilitating factor. Lastly, providing detailed information about the candidate’s future career means having attractive content, cultivating the company’s reputation, publishing clear job advertisements that are not too restrictive and, above all, remaining honest and not overselling the company or position. In this new context, companies must be able to promote internal creativity and respond quickly to external candidates. Indicators must be visible.

(2) Employee commitment also often comes up. This point appears to have emerged more recently, in particular via CSR indicators (which are, incidentally, mandatory) and the search for meaning, which requires greater cross-functionality in collaborations. Here, artificial intelligence will make it possible to obtain useful information to feed and shape the CSR theme, i.e. build a trajectory for it. HR will initiate CSR analyses and forecasts. In this context, it will be necessary to monitor CSR trends, benchmark and industrialise employee engagement indicators and make projections. The development of the employer brand will be one of the goals of the development of collaborative CSR tools. For all this, AI can be extremely useful. Here too, technology will contribute to employee commitment, which will be all the better since juniors as well as seniors will be involved in the drive for CSR.

Talking of seniors: (3) mobility after 20 years in the same position is also a point often raised. Some managers want to adapt, while others prefer to change position and follow more “multiple career” type pathways. Consequently, we must master the age pyramid and the management of failure by analysing in detail each employee segment’s life cycles against the customer life cycle, etc. The development of career paths with subsidiaries is one of the prerequisites: refining and developing multidisciplinarity through learning the new behavioural HR paradigms will make it possible to better plan for the jobs of tomorrow. This naturally implies training and developing geographical mobility, while creating career paths and training paths for these new HR paradigms, because talent must also be retained. BNP has introduced a new possibility: retiring and building loyalty but above all leaving slowly and gradually. Other proposals include developing coaching and mentoring. Here, AI can be a formidable tool for analysing and projecting appropriate resources and relevant and effective processes to provide meaningful responses.

(4) With regard to diversity and equal opportunities, a fourth point that often comes up, the law requires the publication of a gender equality index. In this respect, the bank has three years to show improvement, otherwise it faces the risk of a fine. The financial stakes are therefore high. Now, diversity can be analysed in several ways: equality in recruitment, mobility, remuneration policies, etc. Differences can also relate to older/younger staff with regard to a given promotion. It is therefore important to look at careers and career development and to analyse the details of remuneration and the principles of good conduct in the field of equality and equal opportunities. We believe that improving equal opportunities rather than equality per se is much more realistic.
The final point concerns (5) the organisation of work and in particular the development of remote working (which only constitutes a subset of the organisation of work). There have been remote working agreements on this subject and some companies are more or less open, with several options. Studies show that the greater the openness, the more attracted young people are and the more recruitment increases. It will be necessary to master the role of trade unionism and support managers in successfully coaching remote teams. Here, the greatest difficulty lies in managing a hybrid team on a daily basis: the role of the camera in teams, optimising very short exchanges and streamlining remote relationships.

We now offer you a series of use cases developed by HR startups [2].

In summary, the use of AI will make it possible to better communicate and encourage employee support through a proactive and participatory approach to the recruitment process. Here, AI applied to big data allows the science of external CV detection and the science of knowledge of internal employees to optimise their buy-in with appropriate action plans. In addition to recruitment, AI in HR can also be used to manage the company’s internal talent, assign them to missions and manage their internal mobility. AI can therefore make HR managers more human, provided they master the information biases inherent in its use. Here is a series of use cases developed by startups still mainly in the United States but which will help us to see more clearly and grow, starting with recruitment, then career management, and finally HR management:

  1. Regarding recruitment: Textio (2014, USA, $29.5 million): tools to help write effective job advertisements and analyse the replies of candidates through the use of language processing (NLP).

Predictive analysis tools are then used to identify talent to hunt, with Entelo (2011, USA, $41 million, opposite) and Gild (2011, USA, $26 million, acquired by Citadel in 2016). This type of tool is based on forecasting techniques using machine learning. Entelo has a search engine that scans individuals’ profiles on the Internet to make use of that information, based on 70 criteria such as the condition of their employer (acquisition, IPO, share price trend and sentiment analysis). The IA aspect of this type of solution is not visible to the candidates approached. These tools empower recruiters. French startup Clustree (2013, France, $11.6 million), launched by Bénédicte de Raphélis Soissan, also uses AI to reconcile supply and demand.

Riminder (2016, France, $2.3 million) is another startup offering to filter CVs by using deep learning to retrieve the structured and unstructured information contained in candidates’ CVs and on the Internet. This enables them to forecast the suitability of CVs for vacancies. These tools use semantic analysis to extract text information from CVs and company recognition to find employer names, email addresses, telephone numbers, positions held, training and diplomas. Their systems are trained to recognise and reconcile a wide variety of functions. The candidates’ proposals are then presented in a criteria grid (experience, soft skills, motivation, training, etc.). Furthermore, Riminder functions are also available as APIs for HR software providers. The training data comes from global sources to avoid any local cultural bias.

Paradox.ai (2016, USA, $13.3 million) has created a recruitment chatbot for managing the qualifying dialogue with candidates. This tool is suited to operative professions such as retail and catering.

Checkr (2014, USA, $149 million) is a startup that checks CVs and analyses the reputations of candidates. It already has more than 10,000 clients with its cloud offering, including Uber. The principle consists of scanning all available public sources to find any inconsistencies, oddities or simply a criminal record.

Bayes Impact (2014, France, $120K) is an original company that wants to use AI for the public good and positions itself as an NGO. Its founder, Paul Duan, made his name by launching a partnership with Pôle Emploi, France’s national employment agency, to facilitate convergence between supply and demand in the job market. The company’s service offering includes a conversational agent that helps job-seekers position themselves in the market and find work that matches their abilities.

Groupe Gorgé (France) is an industrial SME specialising in civil and military robotics. In 2020, it launched StedY.io, an AI-based tool for automating the engineer recruitment process, bearing in mind that StedY itself employs engineers.

IBM Watson offers useful personality analysis tools in the form of its Personality Insights and Tone Analyzer APIs, which can be used to analyse the texts written by a person. The solution can detect the author’s mood, such as sadness. It can be used to improve the recruitment selection process, at least of candidates who have a public life on the Internet. Personality analysis can also make use of interview videos, even if the candidate is speaking to a machine as in a serious gaming game. This is what the American company HireView (2004, USA, $93 million) offers with its software, which analyses facial expressions and identifies personality traits. The solution is used at Unilever in the USA and UK. The effectiveness of this type of recruitment based on the person’s appearance should be viewed with caution. The story could become even more complicated if recruiters begin using variations of these facial analysis systems such as this Stanford prototype that automatically determines sexual preferences. Recruitment is another playground for chatbots such as that which the French agency TheChatbotFactory has deployed in the French banking group BNP. In the USA, Google is also present in this market with Google Hire, which was launched in July 2017 and is especially intended for SMEs that use Google Workspace (formerly G Suite), Google’s online business software suite. The recruitment process therefore naturally integrates into Gmail and Google Calendar to dispatch job interviews to the people available in the company.

Google Hire also optimises the text of its job offers, if only for indexing in Google Search! Lastly, Google Hire manages a pool of candidates so that they stand out when new vacancies appear. On the face of it, it is a collaborative work application rather than an AI system, but it offers various means of analysis. Researchers manage to do that simply by analysing eye movements! These systems are weakened by bias caused by the training data. Google emphasises that it relies on AI, if only in terms of its language analysis functions. From a symmetrical point of view, Microsoft and its subsidiary LinkedIn use its database to advise users when writing their CVs (videos) in Word using the Resume Assistant. This is only one of the tools that Microsoft could offer to facilitate recruitment. And as it has the LinkedIn database, it can make full use of it!

Manpower subsidiary Experis IT has developed a solution in which an avatar conducts hiring interviews, similar to L’Oréal’s and Crédit Agricole’s attempts in 2007 using Second Life. Its Digital Room, which provides a ‘cocoon’ isolating the candidate, analyses the person’s face and voice as well as his or her answers to the questions. The system then generates a report for the recruiter and the candidate. This is clearly suited to recruiting candidates for operative functions. It makes you want to use it! This digital innovation was presented at the Viva Technology convention in May 2018. The downside is that this device is needed, but it should be possible to do the same thing remotely using a standard laptop.

Goshaba (2014, France) offers a solution for recruiters that matches the CVs of candidates with job vacancies. It also offers a mobile game for assessing candidates’ social skills. There may be some AI in its solutions, but this is not easy to see.

Merito (2016, France, €2.2 million) helps recruit part-time workers for the distribution industry. Its matching uses distance concepts as well as the assessments of previous managers.

Cryfe (2020, Switzerland) is a behavioural analysis software solution intended for HR and other professionals who may need it (psychologists, communication specialists, politicians, etc.). It uses deep learning in language processing and image analysis to detect the interlocutor’s authenticity. DeepScore (Japan) proposes an equivalent solution. Golden Bees (2015, France, €1 million) offers the Wan2Bee solution, which targets candidates via programmatic advertising. This tool is aimed at potential recruits, who see job vacancy ads instead of traditional online ads. Attract talents select talents manage careers train employees evaluate employees apply.

The Fairhire solution offered by Nottx (2015, UK) is based on AI, which identifies parts of CVs that must be deleted, such as the candidate’s identity, social and geographical origin and training courses taken. The alternative solution would be to introduce a controlled positive bias to the training data, for example, by increasing the statistical weighting of excessively small populations in the business lines. This is what pymetrics (2011, USA, $56 million) seems to propose with its solution that explicitly aims to increase diversity in corporate recruitment. Lastly, we should also mention that an Inclusive AI label has been created for the recruitment industry by Arborus and Bureau Veritas, the latter of which charges a fee for conducting audits.

2. Regarding career management, other AI-based applications aim to improve the matching of employee skills and potential with their career path within the company. WiserSkills (2016, France) has designed a solution that maps the skills that must be developed within the company and uses this information to prepare employees to adapt accordingly. This is an online tool in which the employees themselves describe their skills and sources of motivation. They do not merely provide information on their professional skills alone. The tool was tested at Société Générale in 2017.

Braincities (2013, France) offers a “caring AI” approach with applications in the HR and finance sectors as well as for Smart Cities. These include a machine learning tool that analyses career paths and matches employees with teams in the technical professions. Another of the startup’s tools analyses text exchanges within the company to associate them with cultural elements.

Leena AI (2015, India) is an HR chatbot that answers questions from company employees. It integrates with Slack or Facebook Workplace. This mainly covers standard corporate processes such as requesting leave and submitting expense claims.

Eightfold.ai (2016, USA, $23.75 million) is a talent pool management tool that draws on data inside and outside the company. Ultimately, all of this is intended to speed up the entire recruitment process and, moreover, reduce recruitment errors.

HelloElton (2018, France) offers an AI-based coach who trains employees in soft skills. Exactly what this AI does remains to be seen. Arborus is an endowment fund launched by the Arborus association and major international corporations in 2010. It promotes gender equality worldwide via the European and international GEEIS (Gender Equality European & International Standard) label.

Seedlink (2013, Netherlands) offers an AI system for predicting employee behaviour. This uses language processing to analyse the answers to open questions in a mobile app. The solution is used at L’Oréal (video).

Pulse (2016, France) ‘takes the pulse’ of employees, using opinion surveys consisting of closed and open questions. Once the replies are interpreted, they can be used to “measure the social climate, predict a resignation, calculate the equilibrium salary, detect the risk of burnout and rate the person-job fit”. This is based on language processing.

Flashbrand (2015, USA) also offers an AI-enabled employee survey tool that provides managers with the questions to ask based on the results of previous surveys. At IBM, an AI solution is said to be able to predict when employees would be about to resign. In fact, this AI solution is used internally at IBM. It is said to be effective in 95% of cases, but the details are not specified. IBM says it has reduced its HR workforce globally by 30%. In addition to its resignation prediction tool, which is probably based on multi-criteria machine learning, IBM’s HR department offers employees the AI-based MYCA (My Career Advisor) virtual assistant, which identifies areas for improving skills, and Blue Match for identifying new internal positions available. Lastly, France’s national employment agency Pôle Emploi uses its database of 8.5 million job-seekers (2016 data) to offer them career paths based on their existing skills and predict their chances of re-entering employment. It also predicts the chances of a recruiter’s job vacancy being filled.

3. Lastly, in the management sector, it should be noted that few AI solutions for management in general are currently available. We have seen that they presently focus on recruitment and career management. However, management could make use of various existing or future AI-based solutions, such as those that streamline collaborative work and improve the prioritisation of tasks. Ultimately, we will probably see the emergence of tools enabling managers to improve their communication. Such solutions are still experimental at this stage, however.

This article is co-authored by Sophie Blouquit-Faligot and Pascal de Lima.

Sophie Blouquit-Faligot is Mission Manager and Pascal de Lima is Chief Economist of CGI Business Consulting

[1] From training officers to recruitment officers, to ergonomics and occupational risk prevention project managers, to career development advisors, HRIS consultants, recruitment consultants, social management controllers, training centre directors, HR directors, teachers, trainers, payroll managers, generalist, HR counsels, HR managers, HRIS managers, personnel administration managers, training managers, diversity managers, career management managers, social relations managers, recruitment managers, international mobility managers, payroll managers and compensation managers. 

[2] Use cases (examples of startups in the article’s field) were found in French in “Les usages de l’intelligence artificielle 2021” (The uses of artificial intelligence 2021), February 2021, Olivier Ezratty.

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Pascal de Lima

Global Economy Expert

Pascal de Lima (PhD economics - Sciences Po) is Chief economist of CGI Business Consulting and Teacher at Aivancity. He is a French economist and knowledge manager (KM). He applies his knowledge of economics to the field of KM to solve management consulting challenges. He lectured economics at Sciences Po in Paris and has also taught economics in several of France's top universities (HEC, ESSEC, Sup de Co, Engineering Schools and PREPA...) for a total of 18 years. As an essayist, he wrote more than 200 Op-Eds for major media outlets in France, 10 books and 5 referenced academic articles. He regularly gives lectures at international economics conferences. He specializes in economic foresight. His work is centered around monitoring and prospective thinking with primary focus on the assessment of the economic, social and environmental impact of innovations. After 14 years in the field of management consulting for the financial and banking sector (Ernst & Young, Cap Gemini, Chief Economist & KM at Arthur D.Little and Altran), he founded Economic Cell in 2013, an idea laboratory and consultancy whose purpose is to study market evolutions in light of economic transformations brought about by innovation. In 2017, he joined Harwell Management as Chief Economist, and in 2020, has become a teacher at Aivancity. He holds a PhD degree in Economics from the Paris Institute of Political Studies (Sciences Po), a Masters in Industrial Economics from Panthéon-Sorbonne Paris 1 and a Masters in Financial engineering from a top French business school.

   

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