How Companies and Job Seekers are Adapting to Artificial Intelligence

May 4, 2026, 21:52
GlobalTechnology

Introduction

Companies and job seekers are increasingly using artificial intelligence (AI) in their professional work. This shift has led to new ways of monitoring employees and created ethical challenges during the hiring process.

Main Body

Many large corporations, including Amazon and Disney, have introduced digital dashboards to track how often employees use AI. For example, KPMG's US advisory division expects staff to use AI on 75% of their working days. However, some reports suggest that employees may enter simple prompts just to make their productivity numbers look better. To solve this, KPMG has introduced innovation awards and is working with the University of Texas at Austin to identify truly advanced ways of using AI. At the same time, there is a disagreement between CEOs and board members regarding the speed of AI adoption. According to a Boston Consulting Group survey, 61% of CEOs feel that their boards are rushing the transition. This tension may exist because some board members lack technical AI knowledge, which leads them to push for faster implementation based on industry hype rather than operational reality. Finally, the recruitment process is also changing. The 2026 Job Seeker Insights Report shows that 78% of candidates use AI during the application process, and 22% use it during live interviews. This is largely a response to employers using automation to screen candidates. Consequently, employers are now focusing more on 'AI fluency,' although 36% of candidates admit to exaggerating their AI skills to get hired.

Conclusion

AI is now a necessary part of the corporate world. However, its rollout is complicated by disagreements between executives and a shift toward AI-driven interactions in recruitment.

Learning

🚀 The 'Sophistication' Shift: Moving from Simple to Complex

To move from A2 to B2, you must stop using basic verbs like say, think, or do and start using precision verbs.

Look at how the text describes a disagreement between bosses. An A2 student would say: "They have a problem because they think differently."

The B2 approach uses these 'Power Words' from the text:

  • Adopting →\rightarrow Adoption: Instead of saying "using a new tool," use adopting. It implies a formal process of starting to use something new.
  • Exaggerating: Instead of saying "lying a little bit," use exaggerating. This is a precise B2 word for making something sound better or bigger than it is.
  • Implementation: Instead of saying "putting the plan into action," use implementation. This is a classic corporate B2 term.

💡 Grammar Upgrade: The "Cause and Effect" Connector

At A2, we use 'so' for everything.

  • A2: "Companies use AI, so candidates use AI too."

B2 speakers use Consequently. It sounds more professional and signals a logical result.

Example from the text:

"Employers are using automation to screen candidates. Consequently, employers are now focusing more on 'AI fluency'."

Pro Tip: Start your sentence with Consequently, followed by a comma to instantly sound more advanced in a business meeting or essay.

🔍 Vocabulary Nuance: 'Hype' vs. 'Reality'

In the B2 level, you need to describe abstract concepts. The text mentions "industry hype."

  • Hype (Noun): Excitement that is often exaggerated.
  • Operational Reality (Noun Phrase): How things actually work in the real world.

When you can contrast a "dream" (hype) with a "fact" (reality) using these terms, you are speaking at a B2 level.

Vocabulary Learning

adapting (v.)
to change or adjust to new conditions or situations
Example:Companies are adapting to artificial intelligence by updating their hiring processes.
monitoring (v.)
to observe and check the progress or quality of something over a period of time
Example:HR departments are monitoring employee use of AI through digital dashboards.
ethical (adj.)
relating to moral principles of right and wrong
Example:The use of AI raises ethical challenges about privacy and fairness.
challenges (n.)
difficult tasks or problems that require effort to overcome
Example:AI implementation presents many challenges, including data security concerns.
dashboards (n.)
control panels that display information and metrics
Example:Digital dashboards help managers see how often employees use AI tools.
innovation (n.)
the introduction of new ideas or methods
Example:KPMG introduced innovation awards to reward creative AI applications.
implementation (n.)
the act of putting a plan or system into effect
Example:The company is working on the implementation of AI‑driven recruitment.
disagreement (n.)
a lack of agreement or conflict between parties
Example:There is a disagreement between CEOs and board members about the speed of AI adoption.
transition (n.)
the process of changing from one state or condition to another
Example:The transition to AI tools is faster than many expect.
tension (n.)
a state of mental or emotional strain, often caused by conflict
Example:The tension between executives can delay decision‑making.
technical (adj.)
relating to a particular subject or skill, especially in science or engineering
Example:Board members lack technical AI knowledge, which hampers progress.
hype (n.)
excessive excitement or publicity about something
Example:Industry hype can lead to unrealistic expectations about AI.
operational (adj.)
relating to the functioning or running of a system
Example:Operational reality often differs from theoretical models.
automation (n.)
the use of machines or software to perform tasks automatically
Example:Employers use automation to screen candidates efficiently.
fluency (n.)
the ability to speak or write smoothly and easily
Example:Job seekers must demonstrate AI fluency to impress recruiters.