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May 16, 2023 12 min AI’s impact on the tech skills of tomorrow AI is fundamentally altering our jobs and the tech skills we need to perform them. New research by ServiceNow and Pearson examines how AI will shape the evolution of workplace expertise over the next five years. AI Research
Overhead view of a woman with a laptop across from a small robot
The changing face of tech talent

Companies worldwide are grappling with a tech talent gap that could cost them $6.5 trillion by 2025, according to IDC. At the same time, automation technologies are disrupting global labor markets, automating some jobs entirely while augmenting others by removing boring, repetitive tasks.

To compensate, business leaders must fundamentally rethink who and how they hire. By reskilling workers and placing them in higher-value roles, they can close the talent gap and position themselves for success in a world defined by human/AI partnership.

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Two women standing apart. One holding clipboard, the other woman looking at phone.
AI makes work more human

Future-proofing the workforce begins with understanding the effect AI will have on the skills employees need in the near future. This will inform how business leaders reskill their employees and hire new tech talent.

Interestingly, the data shows that as automation eliminates repetitive tasks, the pendulum will swing toward the distinctly human skills of communication, creativity, and analytical thinking. Simply put, the more we allow machines to do the kinds of things they’re good at, the less humans will have to behave like machines.

By taking on highly technical tasks, programs such as ChatGPT can open the door for people who have been overlooked by the tech industry. Business leaders can bridge the talent gap by tapping into new sources of talent—including non-tech workers whose skills transfer nicely into a more human-centric tech world.

Male walking holding a backpack over shoulder
The more we allow machines to do the kind of things they’re good at, the less humans have to behave like machines.
Insight into the global labor market

To fully understand AI’s effect on the skills and tech positions of the future, ServiceNow’s research partner, Pearson, tracked the likely impact of 16 disruptive technologies on more than 6,500 occupations in the U.S, U.K., Germany, India, Australia, and Japan.

Pearson’s data scientists then created machine learning models to analyze the more than 30,000 skills and 26,000 tasks required to do these jobs, predicting the effect on each from automation and augmentation, and identifying the easiest migration paths to jobs of the future.

Man in suit walking
Insight into the global labor market
Workforce Data Census and labor market datasets were sourced from the governments of U.S., U.K., Germany, Australia, India, and Japan.
Occupations 5, 608
Occupations (5,608) Using each country’s granular census or labor market data, we can map the distribution of jobs to our proprietary ontology. Our ontology is kept up to date by the processing of 10M job ads each month.
Tasks 26,620
Tasks (26,620) Jobs are made up of tasks — discrete activities that require specific skills, knowledge and personal attributes to perform.
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AI-driven modeling of technological transformation
tech impact - automation, augmentation, and added jobs
Tech Impact
  • Automation
  • Augmentation
  • Added Jobs
The tech worker deficit, country by country

Technology has shaped the workforce throughout history, perhaps no more so than today. Every industry will feel the push and pull of automation—some jobs will be eliminated, others augmented, and many created.

That said, not all countries will be affected equally. The data below reflects the total number of jobs—both traditional and tech-related—that could be augmented or automated, and how the effects will be balanced out with the growing demand for tech talent.

By taking into account the existing tech talent gap and combining it with the tech jobs needed to support the growing demand for global digital transformation, we find that automation will create new opportunities. With the right reskilling, non-tech workers whose jobs are affected by AI can step into the tech roles of the future.

USA
United States deficit of workers
Stacked bar chart comparing workforce composition in 2025 and 2027, with three callout stats. By 2027: 23.5M FTEs in automatable roles will need reskilling, 4.9M additional capacity will be gained through augmentation, and 5.9M new tech jobs will be added — all requiring training and upskilling.
GBR
United Kingdom deficit of workers
United Kingdom deficit of workers A workforce data visualization for the United Kingdom comparing 2025 and 2027 projections. Highlights 5M automatable FTEs needing reskilling, 1.3M capacity gain from augmentation, and 1.2M potential new tech jobs requiring training.
DEU
Germany deficit of workers
Germany deficit of workers A workforce data visualization for Germany comparing 2025 and 2027 projections. Shows 5M automatable FTEs needing reskilling, 1.3M capacity gain from augmentation, and 1.2M potential new tech jobs — all requiring upskilling and training.
IND
India deficit of workers
India deficit of workers A workforce data visualization for India comparing 2025 and 2027 projections. Key figures: 16.2M FTEs in automatable roles needing reskilling, a 4.6M capacity gain from augmentation, and 4.7M potential tech jobs added requiring training.
AUS
Australia deficit of workers
Australia deficit of workers A workforce data visualization for Australia comparing 2025 and 2027 projections. Highlights include 1.4M automatable FTEs needing reskilling, 0.3M capacity gain from augmentation, and 0.4M potential new tech jobs that will also require training.
JPN
Japan deficit of workers
Japan deficit of workers A workforce data visualization for Japan comparing 2025 and 2027 projections. Key stats: 7.9M FTEs automatable and needing reskilling, 2M capacity gain from augmentation, and 1.6M potential tech jobs added — all requiring training and upskilling.
Talent transformation by industry

Industries across countries will be affected by AI differently.

In the U.K., Japan, and the U.S., automation will affect twice as many workers in retail as in any other major industry. But it will also create twice as many new tech jobs for people who know how to put these technologies to work. In fact, 1 million additional full-time tech jobs will be created to support the implementation of emerging technologies in the U.S. retail industry.

In India, however, where physical processes have yet to be as altered by automation as they are in other countries, the manufacturing industry will experience the greatest change. Click below to see how industries will fare by country.

USA
United States Productivity gains from automation and augmentation through 2027
A bubble chart plotting five industries by automation percentage and capacity gain. Wholesale and retail trade stands out with the highest capacity gain (7.5%) and 6.3M workers affected. Other industries cluster at lower capacity gains: Manufacturing (2.6M), Accommodation and food service (2.3M), Administrative and support services (1.8M), and Health and social care (2.1M)
GBR
United Kingdom Productivity gains from automation and augmentation through 2027
A bubble chart showing the UK's projected productivity gains through 2027. Wholesale & retail trade leads with 1.12M workers impacted, followed by Professional & technical services (524K), Administrative & support services (512K), Manufacturing (498K), and Health & social care (400K).
DEU
Germany Productivity gains from automation and augmentation through 2027
A bubble chart showing Germany's productivity gains through 2027 by sector. Manufacturing leads at 1.37M workers, closely clustered with Wholesale & retail trade (769K), Professional & technical services (484K), Administrative & support services (380K), and Health & social care (493K) — all grouped at higher capacity gain percentages.
IND
India Productivity gains from automation and augmentation through 2027
A bubble chart showing India's productivity gains from automation and augmentation through 2027. Manufacturing leads with 3.74M workers impacted, followed by Agriculture, forestry & fishing (3.65M) and Wholesale & retail trade (1.88M). Construction, Transportation & storage, and International organization services are also plotted.
AUS
Australia Productivity gains from automation and augmentation through 2027
A bubble chart showing Australia's projected productivity gains through 2027 by sector. Wholesale & retail trade has the highest worker impact at 384K, followed by Manufacturing (142K) and Finance & insurance (143K). Health & social care, Transportation & storage, and Professional & technical services are also featured.
JPN
Japan Productivity gains from automation and augmentation through 2027
A bubble chart showing Japan's productivity gains from automation and augmentation through 2027, plotted by automation % and capacity gain %. Wholesale & retail trade leads with 2.3M workers impacted, followed by Manufacturing (1.82M). Other sectors include Health & social care, Transportation & storage, Accommodation & food service, Finance & insurance, and Other service activities.
Circle size indicates number of automatable jobs.
*Capacity gain is time freed up from use of augmentation technologies
New roles lead to new opportunities

The global workforce is at an inflection point, with AI driving opportunities for those with access to the right training.

Consider this: By 2027, within the ServiceNow ecosystem in the six countries surveyed, more than 1 million additional jobs matching existing roles will be required to support advances in technology. In addition, the research identified eight in-demand roles for which ServiceNow currently doesn’t have skills profiles. Over five years, these future roles will create more than 1.5 million jobs across our surveyed markets.

Based on this data, Servicenow is working to expand its skills portfolio, worker profiles, and credentials—but this is not a ServiceNow-specific phenomenon. As AI reshapes jobs and the expertise needed to perform them, business leaders should prepare by developing the training pathways their employees need to successfully reskill for these future roles.

Talent requirements by role in 2027
A stacked bar chart showing jobs added across current and future ServiceNow roles in five countries — USA, GBR, IND, DEU, and JPN. Current roles include Application Developers, Implementation Engineers, Technical Architects, System Administrators, and Process Analysts. Future "net-new" specializations include Data Analysts, Platform Owners, Product Owners, and more. Application Developers lead with roughly 265K jobs added across all markets.
Tapping into transferable business skills

Now that we understand which industries will be affected by AI, we can identify workers in each of those industries whose skills are the most easily transferable to the tech jobs of the future.

For example, we know that manufacturing will be a highly affected industry in India. But our research shows that fishery workers in India have the core skills to become help-desk agents. Developing these and other career migration paths is especially important given the effect of automation on these positions and the need for new tech talent across the board.

USA
Reskilling opportunities in the United States
A horizontal bar chart titled "Reskilling opportunities in the United States" showing six at-risk job categories — Bookkeeping Clerks (778K), Secretaries (648K), and Registered Nurses (306K) — alongside their top matched ServiceNow roles and job fit percentages. Most roles map to Help Desk Support Agents or Change Managers, with skill overlap ranging from 64% to 82%
GBR
Reskilling opportunities in the United Kingdom
A horizontal bar chart titled "Reskilling opportunities in the United Kingdom" showing six at-risk roles in 2027, including Accounts Clerks (206K) and Bookkeepers (128K). Most roles map to Help Desk Support Agents or Change Managers, with job fit scores ranging from 61% to 82%.
DEU
Reskilling opportunities in Germany
A horizontal bar chart titled "Reskilling opportunities in Germany" showing six at-risk roles in 2027 — including Healthcare & Nursing (99K) and Postal & Delivery Services (103K) — mapped to ServiceNow roles like Machine Learning Engineers and Help Desk Support Agents, with job fit scores between 61% and 74%.
IND
Reskilling opportunities in India
A horizontal bar chart titled "Reskilling opportunities in India" highlighting six at-risk roles in 2027, including Dairy & Livestock Producers (447K) and Fishery Workers. Top matched ServiceNow roles are mostly Help Desk Support Agents and Change Managers, with job fit scores ranging from 62% to 75%.
AUS
Reskilling opportunities in Australia
A horizontal bar chart titled "Reskilling opportunities in Australia" showing six at-risk roles in 2027 — including Accounts Clerks (44K) and Retail Managers (33K) — and their top matched ServiceNow roles. Matches include Help Desk Support Agents, Machine Learning Engineers, and Change Managers, with job fit scores between 64% and 85%.
JPN
Reskilling opportunities in Japan
A horizontal bar chart titled "Reskilling opportunities in Japan" showing six at-risk job categories in 2027, including Retail Salespersons (1.23M) and Accounting Clerks (700K), alongside their top matched ServiceNow roles. Most map to Help Desk Support Agents or Change Managers, with job fit scores ranging from 61% to 75%.
AI’s impact by role

The research has also revealed ways in which certain existing positions will evolve when augmented by AI.

Using the role of system administrator as an example, we found that 9.3% of their current tasks could be automated and 39.7% of their tasks could be augmented. This will lead to up to 13 hours each week being freed up by AI automation and augmentation. Based on an analysis of 32 capabilities identified as crucial to all roles of the future, sysadmins must be highly proficient in these five areas by 2027:

  • Foundational IT skills
  • Cyber awareness
  • Digital collaboration
  • Digital communication
  • Learning

Ideally, sysadmins should use this opportunity to learn new skills or train for a new role to help move
the business forward. On the flip side, business leaders should identify opportunities to keep their sysadmins motivated, engaged, and on a career growth plan. When viewed through this lens, upskilling to relevant, future-demand roles is key to staff retention.

System administrator
AI’s impact by task, time, and proficiencies System administrator
Two pie charts and a callout box summarizing automation's workforce impact. The first shows task impact: 51% unimpacted, 39.7% augmented, and 9.3% automated. The second shows hours freed by automation: 13% freed, 27% unchanged. A side panel lists five areas of proficiency needed by 2027 — foundational IT, digital collaboration, learning, machine learning & AI, and statistics & predictive models.
App developer
AI’s impact by task, time, and proficiencies App developer
Two pie charts showing AI's impact on App Developer tasks and time. 80.6% of tasks are unimpacted, 17% augmented, and 2.4% automated. Automation frees up 4.2% of hours. Five proficiencies needed by 2027: foundational IT, statistics & predictive models, machine learning & AI, cyber awareness, and programming.
Process analyst
AI’s impact by task, time, and proficiencies Process analyst
Two pie charts showing AI's impact on Process Analyst tasks and time. 81.2% of tasks are augmented, 18.8% automated, and a small share unimpacted. Automation frees up 3.3% of hours. Five proficiencies needed by 2027: foundational IT, statistics & predictive models, machine learning & AI, cyber awareness, and programming.
Implementation consultant
AI’s impact by task, time, and proficiencies Implementation consultant
Two pie charts showing AI's impact on Implementation Consultant tasks and time. 76% of tasks are unimpacted, 12.3% augmented, and 11.7% automated. Automation frees up 6.8% of hours. Five proficiencies needed by 2027: personal learning & mastery, achievement focus, foundational IT, agility, and collaboration.
Implementation engineer
AI’s impact by task, time, and proficiencies Implementation engineer
Two pie charts showing AI's impact on Implementation Engineer tasks and time. 78.2% of tasks are unimpacted, 17% augmented, and 4.8% automated. Automation frees up 5% of hours. Five proficiencies needed by 2027 include foundational IT, critical thinking, digital collaboration, learning, and digital communication.
Junior app developer
AI’s impact by task, time, and proficiencies Junior app developer
Two pie charts showing AI's impact on Junior App Developer tasks and time. 72.6% of tasks are unimpacted, 25.7% augmented, and 1.7% automated. Automation frees up 5.5% of hours. Five key proficiencies needed by 2027: foundational IT, statistics & predictive models, machine learning & AI, cyber awareness, and programming.
Technical architect
AI’s impact by task, time, and proficiencies Technical architect
Two pie charts showing AI's impact on Technical Architect tasks and time. 76.6% of tasks are unimpacted, 18.7% augmented, and 4.7% automated. Automation frees up 5% of hours. Five proficiencies needed by 2027 include foundational IT skills, cyber awareness, digital collaboration, digital communication, and learning.
Master architect
AI’s impact by task, time, and proficiencies Master architect
Two pie charts showing AI's impact on Master Architect tasks and time. 81% of tasks are unimpacted, 9.7% augmented, and 9.3% automated. Automation frees up 13% of hours. A side panel lists five proficiencies needed by 2027: digital communication, cyber awareness, research & problem solving, operationalizing data, and learning.
From the mailroom to sys admin standout Meet Cheyenne Saulnier

Cheyenne Saulnier always had a penchant for technology, but she never thought she would find her place in the IT industry. After all, she was working in the mailroom—not your traditional route to a high-paying tech position. When her strong communication and service skills were noticed by IT leaders within her organization, she was invited to train as a ServiceNow system administrator.

Cheyenne’s story is notable but not unique. As technology platforms become more accessible, it becomes easier for people without programming and other tech-related backgrounds to work in IT. All they need is a desire to learn and access to the right training programs.

Tech talent training for 2027

As AI becomes more embedded in the workplace, leaders who ignore its impact on the workforce do so at their own peril. Yet, while disruption is inevitable, there will be tremendous opportunities to create new, more human—and, yes, more productive—ways of working.

ServiceNow University is a new global training initiative created to spark our tech talent transformation. By building comprehensive programs accessible to anyone with the desire to learn, we open doors to the tech roles of the future. When we connect with and cultivate a new breed of IT worker, we fill the tech talent gap—and that’s a win for our organization, employees, partners and, ultimately, our customers.

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