Rebooting employees: upskilling for artificial intelligence in multinational corporations

Figures & data

Table 1a. Participant’s and their company’s characteristics.

Participant number	Company headquarter	Headcount worldwide	Headcount in India	Gender	Experience (in years)	Job function	Experience of AI implementation	Experience working with AI-enabled services
1	USA	2100	1500	Male	13	Technical	7	7
2	USA	27,000	750	Male	16	Technical	3	3
3	Denmark	100	50	Male	11	Managerial	2	3
4	Ireland	505,000	150,000	Male	20	Managerial	2	2
5	India	243,000	215,000	Male	14	Managerial	2	3
6	USA	500	450	Male	15	Technical	3	3
7	Canada	77,000	13,500	Female	15	Managerial	2	2
8	USA	450,000	140,000	Female	19	Technical	2	2
9	USA	23,000	18,000	Female	10	Managerial	2	3
10	Switzerland	147,000	10,000	Male	12	Technical	2	1
11	Ireland	505,000	150,000	Female	11	Managerial	3	3
12	USA	450,000	140,000	Male	14	Technical	2	4
13	USA	500	450	Male	13	Managerial	2	2
14	USA	800	400	Female	10	Managerial	1	2
15	India	447,000	375,000	Male	42	Managerial	7	7
16	USA	23,000	18,000	Female	20	Managerial	6	6
17	USA	23,000	18,000	Male	26	Managerial	2	2
18	USA	292,000	194,700	Male	28	Managerial	2	4
19	France	122,000	25,000	Female	20	Technical	3	5
20	France	45,000	6,000	Female	13	Technical	2	2

Figure 1. Data structure.

Table 1b. Post-study participants’ profile.

Participant number	Company headquarter	Headcount worldwide	Headcount in India	Gender	Experience (in years)	Job function	Experience of AI implemen­tation	Experience working with AI-enabled services
1	USA	23,000	18,000	Male	17	Managerial	7	6
2	India	243,000	215,000	Female	13	Managerial	5	5
3	Canada	77,000	13,500	Male	15	Technical	3	2
4	USA	450,000	140,000	Male	24	Technical	6	6
5	United Kingdom	80,000	20,000	Female	15	Managerial	3	3

Table 2. Data supporting interpretations of skills identification for upskilling for AI.

Themes	Representative quotations
Technological skills essential for upskilling
Data analysis skills	‘Through data analysis, we discover useful information…use it for [data] interpretation and that provides us a concrete basis for taking decisions’ (Participant 19)
	‘Data is the key for any business to be successful today…the analysis is useful for predictive modeling’ (Participant 3)
	‘The current skill needed for professionals is in machine learning and developing models…but the real application is in making better predictions using those models…so data analysis for predictive modeling is the most important skill for the future’ (Participant 11)
Digital skills	‘The digital skill that is picking up today and will be most important in the future is cloud automation….cloud automation empowers developers and managers to deliver services and meet business demands through end-to-end automation’ (Participant 12)
	‘Digital skills will enable transformation in Industry 4.0…it’s a combination of multiple skills including front-end skills like immersive experience [through] augmented reality/virtual reality…[and] mobility skills across different devices…and back-end skills like intelligent automation, machine learning, robotic process automation and so on….’ (Participant 16).
Cognitive skills essential for upskilling
Complex cognitive skills	‘A design thinking mindset provides an innovative approach to problem-solving….it involves designing, prototyping, and testing out-of-the-box ideas….basically, it’s like an ongoing experiment that helps in the decision making process’ (Participant 15)
	‘We use algorithms to transform data through cognitive computing….our AI-assistant is a smart assistant that runs on big data and Internet-of-Things…as of now, it is about 80-85% accurate in understanding the user’s demands and responds accordingly…going forward with improved accuracy, AI-assistants will be of immense support to us for complex data processing’ (Participant 4)
	‘Humans process information at multiple levels including cognitive, subconscious, and shared cognitive….these also include biases…in future when AI will handle basic data well, complex processing skills for meaningful insights will become very important for humans’ (Participant 11)
Decision making skills	‘Presently AI’s biggest challenge is to overcome biases…data fed into all AI-systems is based on prior experiences of humans which are biased…so, despite all advancements in technology, the AI-based outcomes are also biased…so this awareness is very important for decision-makers’ (Participant 1)
	‘Decision making is highly contextual…data must be understood in the right context…also there are ethical aspects and human behaviour….all need to be considered for good decision making’ (Participant 19)
Continuous learning skills	‘As an HR manager, my key role is to identify employees who are stagnant…it is my responsibility to help them transform….equipping [them] with new skills and expertise’ (Participant 11)
	‘We encourage horizontal movement in the organization across domains…picking up things quickly in different situations or projects shows flexibility and versatility’ (Participant 15)
	‘Continuous learning was always important and will continue to remain important…else we cannot survive in this industry’ (Participant 20)
Evergreen skills for upskilling
Interpersonal skills	‘AI is making everything data-driven…personal judgments and feelings will have no place soon….still as humans, we will continue to understand others and empathize with them’ (Participant 2)
Communication skills	‘Whatever be the case…personal touch, personal communication is very much needed to maintain a good culture and work environment…if there is a problem, we need humans to solve it….moreover, a chat robot (chatbot) cannot connect with me [psychologically or emotionally] through text messages’ (Participant 19)
Leadership skills	‘Let’s say tomorrow a robot is in your team and is reporting to you….[as a leader] How much of autonomy will you give to the robot and to the human? How will you personalize things for human employees? Leading a mix of robots and humans would be a different ball game altogether’ (Participant 16)
Skills not required for upskilling
Basic statistics skills	‘Need for basic skills is there today but diminishing soon…basic statistics will be handled well by AI in the future…humans must do things they are better at’ (Participant 11).
	‘All routine jobs are being replaced by AI….just knowing statistics is not enough….what is relevant is the application of statistics’ (Participant 16)
Project management skills	‘Traditional project management is dying now….it was very important a few years back but things like scheduling, resource allocation is being automated now…the only role of project manager remains in handling any crisis kind of a situation…like when a resource suddenly leaves the company…then to find a replacement…Scrum master is replacing project manager as development is happening in short sprints’ (Participant 5)
	‘Two skills that today’s and future managers cannot skip are Agile Coach and Scrum Master….(we sought an explanation of these skills)….agile coach creates [and] facilitates agile processes within an organization….Scrum master is a type of agile coach who implements agility at team level…’ (Participant 20)

Figure 2. Relative importance of skills for employee upskilling.

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article. Further details may not be available as it will compromise the privacy of the research participants. For further clarifications, please contact the lead author.