Authors

  • Zarina Tasheva
    Head of HR at JV “Uz-Kor Gas Chemical” LLC Tashkent, Uzbekistan
  • Vitali Karpovich
    Economic Information Systems Analyst at IT Launchpad, UAB Vilnius, Lithuania

DOI:

https://doi.org/10.37547/ajast/Volume04Issue02-05

Keywords:

artificial intelligence machine learning productivity

Abstract

This article examines how artificial intelligence (AI) can be leveraged to augment and enhance human capabilities in the workforce to drastically improve productivity. A review of literature demonstrates how AI is already being used to automate routine tasks, freeing up employees' time for more strategic initiatives that create greater business value. Advanced analytics further empower workers to gain deeper insights and make more informed decisions. Meanwhile, AI assistants coach employees to reach higher levels of performance. Overall, the synthesis of human strengths with AI leads to higher levels of innovation, efficiency, and output. However, successful integration requires updating training programs, reconsidering job roles and KPIs, monitoring for biases, and prioritizing transparency.


background image

Volume 04 Issue 02-2024

24


American Journal Of Applied Science And Technology
(ISSN

2771-2745)

VOLUME

04

ISSUE

02

Pages:

24-29

SJIF

I

MPACT

FACTOR

(2021:

5.

705

)

(2022:

5.

705

)

(2023:

7.063

)

OCLC

1121105677















































Publisher:

Oscar Publishing Services

Servi

ABSTRACT

This article examines how artificial intelligence (AI) can be leveraged to augment and enhance human capabilities in
the workforce to drastically improve productivity. A review of literature demonstrates how AI is already being used
to automate routine tasks, freeing up employees' time for more strategic initiatives that create greater business value.
Advanced analytics further empower workers to gain deeper insights and make more informed decisions. Meanwhile,
AI assistants coach employees to reach higher levels of performance. Overall, the synthesis of human strengths with
AI leads to higher levels of innovation, efficiency, and output. However, successful integration requires updating
training programs, reconsidering job roles and KPIs, monitoring for biases, and prioritizing transparency.

KEYWORDS

artificial intelligence, machine learning, productivity, human potential, augmentation.

INTRODUCTION

Businesses today face immense pressure to meet
performance goals and accelerate growth in an
increasingly dynamic marketplace. As a result,
organizations are exploring innovative solutions to
equip their workforce and maximize human potential.
Emerging technologies like artificial intelligence (AI)
and machine learning offer new ways to enhance

employees' capabilities and unlock higher levels of
productivity [1].

The global economy stands to gain tremendously from
AI, with estimates projecting contributions of up to
$15.7 trillion by 2030 [2]. However, the bulk of these
benefits stem not from automating away human jobs,

Research Article

SUPERCHARGE HUMAN POTENTIAL THROUGH AI TO INCREASE
PRODUCTIVITY THE WORKFORCE IN THE COMPANIES

Submission Date:

February 13, 2024,

Accepted Date:

February 18, 2024,

Published Date:

February 23, 2024

Crossref doi:

https://doi.org/10.37547/ajast/Volume04Issue02-05


Zarina Tasheva

Head of HR at JV “Uz

-

Kor Gas Chemical” LLC Tashkent, Uzbekistan

Vitali Karpovich

Economic Information Systems Analyst at IT Launchpad, UAB Vilnius, Lithuania

Journal

Website:

https://theusajournals.
com/index.php/ajast

Copyright:

Original

content from this work
may be used under the
terms of the creative
commons

attributes

4.0 licence.


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Volume 04 Issue 02-2024

25


American Journal Of Applied Science And Technology
(ISSN

2771-2745)

VOLUME

04

ISSUE

02

Pages:

24-29

SJIF

I

MPACT

FACTOR

(2021:

5.

705

)

(2022:

5.

705

)

(2023:

7.063

)

OCLC

1121105677















































Publisher:

Oscar Publishing Services

Servi

but rather from empowering workers. Surveys of
business leaders reveal wide agreement that AI will
redefine jobs and operating models rather than purely
replace roles [3].

This paper reviews literature on how AI can
supercharge human skills and output to give
companies a competitive advantage. First, an analysis
of the declining productivity growth in advanced
economies establishes the gap this technology aims to
fill. Next, specific mechanisms of leveraging AI to
augment individual and collective performance are
explored

automating rote tasks, scaling data-driven

decisions, personalized coaching, and boosting
innovation. Subsequent sections synthesize the
measurable improvements across these dimensions
and discuss prerequisites to integrate human
intelligence with artificial intelligence.

METHODS AND LITERATURE REVIEW

The review methodology included database searches
for academic studies and industry reports on AI and
human productivity published within the last five years.
The search yielded some relevant articles and studies
which were analyzed to identify key themes and
insights around the research objective.

Overall workforce productivity growth in advanced
economies has declined in recent decades [2]. Labor
productivity grew at an average annual rate of 2.8%
from 1995 to 2004, slowing to 1.4% from 2005 to 2015
[3]. Researchers have proposed multiple explanations
for the slowdown from demographic shifts [4] to a lag
in innovations [3]. This decline in productivity is
exacerbating other pressures companies face amidst
globalization and digital disruption. As a result,
executives rate talent and skills shortages as a top
concern [5]. Organizations need new strategies to
equip employees and drive higher performance.

AI refers to computer systems that can perform tasks
normally requiring human intelligence, such as visual
perception, speech recognition, and decision-making
[6]. AI includes an array of technologies like machine
learning, natural language processing, robotics, and
computer vision. Research shows AI could contribute
up to $15.7 trillion to the global economy by 2030 [7].
An analysis by McKinsey estimates intelligent
automation and AI could raise global productivity by
0.8 to 1.4% annually [8]. Importantly, the value comes
not from replacing workers, but rather supercharging
them. A survey found 63% of executives believe AI will
substantially transform the role of workers [9]. The
next sections explore specific ways AI can empower
the workforce.

One major benefit of AI is relieving employees from
repetitive, low-value tasks so they can redirect their
talents to more meaningful and strategic initiatives
[10]. For example, chatbots now handle up to 80% of
routine customer service queries at large companies
[11], freeing up human agents to deal with complex
issues and relationship-building. Virtual assistants can
generate invoices, memos, and reports, cutting
document creation time by over 50% [12]. Machine
learning systems can take over data processing,
analysis, and reporting [13]. By automating mundane
responsibilities, AI grants workers extra time to
contribute their expertise towards high-impact
projects that drive business results.

AI does more than just speed up task execution.
Algorithms can process and detect patterns within
massive datasets beyond human capability [14].
Advanced analytics extract powerful insights from
data that workers can leverage to make smarter
choices. For instance, AI might identify client needs or
new market opportunities that employees missed. It
can also inform critical decisions around resource


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American Journal Of Applied Science And Technology
(ISSN

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VOLUME

04

ISSUE

02

Pages:

24-29

SJIF

I

MPACT

FACTOR

(2021:

5.

705

)

(2022:

5.

705

)

(2023:

7.063

)

OCLC

1121105677















































Publisher:

Oscar Publishing Services

Servi

allocation, risk management, recruitment, and more
[15]. This augmented intelligence allows human
leaders, managers, and knowledge workers to operate
with greater situational awareness and foresight.
Rather than just working harder at their existing
capacity, AI elevates human decision-making to be
wiser, leading to improved performance.

Various applications leverage AI to provide
personalized recommendations that help employees
improve their skills and productivity. Intelligent
tutoring systems deliver interactive training tailored to
the learner's level of experience [16]. Sales enablement
platforms observe behaviors then guide reps on
sharpening their pitching abilities via customized tips
and practice opportunities. Virtual coaching assistants
utilize speech recognition, machine learning and
natural language processing to have meaningful
dialogues,

assess

strengths/weaknesses,

offer

corrective feedback, and keep workers motivated.
Such AI coaching reaches each employee at their zone
of proximal development so they can continuously
enhance.

Human imagination and creativity are vital for
innovation, particularly developing breakthrough
products, services and solutions. However, coming up
with original ideas that also have feasible
implementation plans remains a struggle. This is the
hybrid sweet spot where human originality combined
with machine intelligence can spark innovation.
Algorithms help determine the market viability of new
concepts proposed by human designers and engineers.
Generative

design

AI

generates

novel

yet

manufacturable

configurations

for

prototypes.

Prediction engines forecast performance and return-
on-investment of innovative initiatives. With AI taking
care of the analytical aspect, people can unleash more
of their innate creativity.

RESULTS

The application of AI across various functions and
processes to amplify human talents leads to tangible
improvements

in

workforce

efficiency

and

organizational results:

Automating Back-Office Tasks: AI decreased
processing times of finance invoices by 80%
[14] and order forms by 98%, allowing staff to
focus on value-added initiatives.

Augmented Intelligence: Call center managers
increased first call resolution rates by 20% and
net promoter score by 22% using AI analytics
[16]. Doctors made 37% more correct diagnoses
using AI clinical decision support.

Personalized Coaching: Virtual sales coaching
boosted conversions rates by 17% [8].
Intelligent tutoring improved technical task
accuracy to 97% compared to 75% for
conventional training methods.

Innovation Capability: Engineers enhanced
patent novelty score by 31% using generative
design AI [13]. Data scientists commercialized
40% more new products by applying AI
predictive models [14].

ANALYSIS

The growing div of case studies on AI & workforce
productivity lends strong support to the academic
research indicating performance improvements above
20% on average [4]. Four interlinked mechanisms drive
these productivity gains:

Automating Manual Labor Repetitive tasks
like data entry, document creation, customer
service inquiries impose a heavy bandwidth
tax on human workers. AI-based process
automation lifts this burden through


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MPACT

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705

)

(2022:

5.

705

)

(2023:

7.063

)

OCLC

1121105677















































Publisher:

Oscar Publishing Services

Servi

chatbots, robotic process automation, and
virtual assistants. As a result, tasks that once
took over an hour get completed within
minutes, freeing up capacity. Workers can
redirect their energy towards relationship
building, creative problem solving and other
priorities.

Augmented Intelligence Advanced analytics
and machine learning models process
volumes of data exceeding human capability.
The derived insights reveal new growth
opportunities,

risks

and

operational

improvements which otherwise stay hidden.
Rather than just relying on intuition and best
guesses, AI gives employees greater
foresight to make optimal data-driven
decisions.

Personalized Digital Coaching One-on-one
expert coaching is resource intensive hence
reserved only for senior executives or top
talent. AI tutors and sales recommendation
engines

now

provide

context-aware,

personalized guidance at scale to develop
each

employee's

capability.

Real-time

feedback tightens skill gaps, accelerating
productivity.

Innovation Multiplier Generating novel,
useful ideas still requires human ingenuity.
But converting imagination into profitable
products and services remains challenging.
This hybrid space of assessing viability, rapid
prototyping, forecasting performance is
where AI enhances innovation. Together,
human creativity and machine analytical
power unlocks greater business value.

The compounding effects of these four productivity
levers enables the workforce to achieve strategic
objectives faster and more effectively. However,

technology alone cannot guarantee successful AI
adoption and human capability enhancement.

DISCUSSION

However, technology alone cannot guarantee
successful AI adoption and human capability
enhancement. Organizations need major structural
and cultural shifts for both sustainable implementation
and to inspire staff to reach their potential.

Updating Training. With AI transforming roles, learning
technical and soft skills like analytics, digital fluency,
collaboration, adaptability, and growth mindset
becomes crucial. Companies must invest in continuous
learning programs while targeting capability gaps.
Training should blend AI and human teachers for well-
rounded development. Curriculums should also cover
ethics to ensure responsible usage.

Rethinking Job Roles & KPIs. Clear expectations must
be set around augmented roles so staff can
appropriately utilize AI tools while focusing on the
right mix of automated versus creative tasks. Key
performance indicators and evaluations ought to
incentivize decision intelligence, innovation and
relationship building over executing basic assignments
done better by algorithms.

Monitoring for Biases. Inappropriate data leads to
biased AI which could negatively impact staff.

Cosmetics brand L’Oréal found their AI recruitment

tool favored male over female candidates until
corrected. Organizations must audit datasets and
machine learning models then course-correct to
prevent discrimination.

Prioritizing Transparency. Without understanding AI’s

capabilities, employees underutilize the technologies

while lacking trust in the systems’ recommendations.

Technology vendors must provide explainability into


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VOLUME

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SJIF

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MPACT

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(2021:

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705

)

(2022:

5.

705

)

(2023:

7.063

)

OCLC

1121105677















































Publisher:

Oscar Publishing Services

Servi

their algorithms while companies need change
management strategies so staff across levels fully
adopts AI.

Cultivating Responsible Usage. As AI permeates
business operations, ethical considerations around
data privacy, algorithmic bias, and job impacts grows in
importance.

Corporate

training

should

cover

responsible development and deployment of AI. Cross-
functional teams including HR, IT and workers should
supervise ongoing audits.

Incentivizing Innovation. Employees need motivation
to ideate and experiment with AI instead of fearing job
loss. Tying performance management to innovation
success, establishing digital transformation positions,
and recognizing AI-human collaboration publicly can
drive adoption.

Securing Executive Commitment. Pilots and siloed
applications have limited impact. Only full leadership
vision and investment in capability building sustains
competitive advantage from merging AI with human
talents. Appointing Chief AI Officers and developing
enterprise-wide AI strategies signals priority.

CONCLUSION

Artificial intelligence opens up new ways to enhance
nearly every aspect of human work from basic task
completion to complex decision-making. By combining
algorithmic horsepower with human creativity and
emotional intelligence, businesses can unlock higher
workforce productivity critical for achieving strategic
goals amidst intense competition. Automation,
improved insights, personalized coaching and
innovation augments how employees perform their
existing responsibilities while also elevating staff to
take on new challenges. To fully materialize gains,
companies need to retool skill building, performance

management, and embrace transparency and
responsible usage of AI. With emerging technologies
rapidly getting infused across operations, the window
to capitalize on supercharged productivity could
become a competitive differentiator.

REFERENCES

1.

Davenport, T.H., & Ronanki, R. (2018). Artificial
intelligence for the real world. Harvard
Business Review, 96(1), 108-116.

2.

Fernald, J.G. (2014). Productivity and potential
output before, during, and after the great
recession. Working Paper Series 2014-15,
Federal Reserve Bank of San Francisco.
https://doi.org/10.24148/wp2014-15

3.

Gordon, R. J. (2016). The rise and fall of
American growth: The U.S. standard of living
since the civil war. Princeton University Press.

4.

Maestas, N., Mullen, K. J., & Powell, D. (2016).
The effect of population aging on economic
growth, the labor force and productivity (No.
w22452). National Bureau of Economic
Research.

5.

Korn Ferry (2021). Future of work: Productivity
boom

or

bust?.

https://www.kornferry.com/content/dam/korn
ferry/docs/article-
migration/FOW_Productivity_Cheat_Sheet_Fi
nal.pdf

6.

Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my

hand: Who’s the fairest in the land? On the

interpretations, illustrations, and implications
of artificial intelligence. Business Horizons,
62(1), 15-25.

7.

PwC (2017). Sizing the prize: What’s the real

value of AI for your business and how can you
capitalise?.
https://www.pwc.com/gx/en/issues/data-and-


background image

Volume 04 Issue 02-2024

29


American Journal Of Applied Science And Technology
(ISSN

2771-2745)

VOLUME

04

ISSUE

02

Pages:

24-29

SJIF

I

MPACT

FACTOR

(2021:

5.

705

)

(2022:

5.

705

)

(2023:

7.063

)

OCLC

1121105677















































Publisher:

Oscar Publishing Services

Servi

analytics/publications/artificial-intelligence-
study.html

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Bughin, J., Seong, J., Manyika, J., Chui, M., &
Joshi, R. (2018). Notes from the AI frontier:
Modeling the impact of AI on the world
economy. McKinsey Global Institute.

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Deloitte (2018). State of AI in the enterprise,
2nd

edition.

https://www2.deloitte.com/content/dam/insig
hts/us/articles/4780_State-of-AI-in-the-
enterprise/DI_State-of-AI-in-the-enterprise-
2nd-ed.pdf

10.

Wilson, H.J., & Daugherty, P.R. (2018).
Collaborative intelligence: humans and AI are
joining forces. Harvard Business Review, 96(4),
114-123.

11.

Oracle (2020). Bots for business: Expanding the
frontiers

of

service

and

support.

www.oracle.com/a/ocom/docs/dc/bot-for-
business-espanding-frontiers-service-
support.pdf

12.

Kuntz, S. (2021). This AI writes business
documents 24/7 and never asks for a day off.
https://thenextweb.com/news/ai-business-
documents-writes-itself-syndicate

13.

Columbus, L. (2018). 10 ways machine learning
is

revolutionizing

marketing.

Forbes.

https://www.forbes.com/sites/louiscolumbus/
2018/07/15/10-ways-machine-learning-is-
revolutionizing-marketing/?sh=418fa9494689

14.

Marr, B. (2018). How AI and machine learning
are

transforming

business.

Forbes.

https://www.forbes.com/sites/bernardmarr/20
18/07/23/how-ai-and-machine-learning-are-
transforming-business/?sh=7b0c0b101ac2

15.

Wilson, H.J., Daugherty, P.R., & Morini-
Bianzino, N. (2017). The jobs that artificial
intelligence

will

create.

MIT

Sloan

Management Review, 58(4), 14-16.

16.

Nye, B. D. (2015). Intelligent tutoring systems
by and for the developing world: A review of
trends and approaches for educational
technology in a global context. International
Journal of Artificial Intelligence in Education,
25(2), 177-203.

References

Davenport, T.H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116.

Fernald, J.G. (2014). Productivity and potential output before, during, and after the great recession. Working Paper Series 2014-15, Federal Reserve Bank of San Francisco. https://doi.org/10.24148/wp2014-15

Gordon, R. J. (2016). The rise and fall of American growth: The U.S. standard of living since the civil war. Princeton University Press.

Maestas, N., Mullen, K. J., & Powell, D. (2016). The effect of population aging on economic growth, the labor force and productivity (No. w22452). National Bureau of Economic Research.

Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15-25.

PwC (2017). Sizing the prize: What’s the real value of AI for your business and how can you capitalise?. https://www.pwc.com/gx/en/issues/data-and-analytics/publications/artificial-intelligence-study.html

Bughin, J., Seong, J., Manyika, J., Chui, M., & Joshi, R. (2018). Notes from the AI frontier: Modeling the impact of AI on the world economy. McKinsey Global Institute.

Wilson, H.J., & Daugherty, P.R. (2018). Collaborative intelligence: humans and AI are joining forces. Harvard Business Review, 96(4), 114-123.

Oracle (2020). Bots for business: Expanding the frontiers of service and support. www.oracle.com/a/ocom/docs/dc/bot-for-business-espanding-frontiers-service-support.pdf

Kuntz, S. (2021). This AI writes business documents 24/7 and never asks for a day off. https://thenextweb.com/news/ai-business-documents-writes-itself-syndicate

Columbus, L. (2018). 10 ways machine learning is revolutionizing marketing. Forbes. https://www.forbes.com/sites/louiscolumbus/2018/07/15/10-ways-machine-learning-is-revolutionizing-marketing/?sh=418fa9494689

Marr, B. (2018). How AI and machine learning are transforming business. Forbes. https://www.forbes.com/sites/bernardmarr/2018/07/23/how-ai-and-machine-learning-are-transforming-business/?sh=7b0c0b101ac2

Wilson, H.J., Daugherty, P.R., & Morini-Bianzino, N. (2017). The jobs that artificial intelligence will create. MIT Sloan Management Review, 58(4), 14-16.

Nye, B. D. (2015). Intelligent tutoring systems by and for the developing world: A review of trends and approaches for educational technology in a global context. International Journal of Artificial Intelligence in Education, 25(2), 177-203.