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Why Companies Are Moving from Fixed Roles to Flexible Expertise
INTERVIEW – PART ONE
Outstaffing and Flexible Staffing in 2026:
Why Companies Are Moving from Fixed Roles to Flexible Expertise
INTERVIEW – PART ONE
Outstaffing and Flexible Staffing in 2026:
Hiring isn't what it was even a few years ago.
As AI reshapes work, markets become more volatile, and businesses face constant pressure to move faster, many organizations are rethinking not only who they hire but how they build teams.
To better understand what's driving this shift,
we spoke with Artem Furs, Account Director at Gitmax, about how hiring priorities have evolved, why traditional recruitment models are becoming less effective, and what businesses are looking for when building teams today.
As AI reshapes work, markets become more volatile, and businesses face constant pressure to move faster, many organizations are rethinking not only who they hire but how they build teams.
To better understand what's driving this shift,
we spoke with Artem Furs, Account Director at Gitmax, about how hiring priorities have evolved, why traditional recruitment models are becoming less effective, and what businesses are looking for when building teams today.
Artem Furs is a recruitment and HR consulting expert with over 15 years of experience in talent acquisition and flexible staffing. He has worked with global companies including Accenture, EY, Danone, and PepsiCo.
Artem Furs,
Account Director at Gitmax
Account Director at Gitmax
Hiring isn't what it was even a few years ago. As AI reshapes work, markets become more volatile, and businesses face constant pressure to move faster, many organizations are rethinking not only who they hire but how they build teams.
To better understand what's driving this shift, we spoke with Artem Furs, Account Director at Gitmax, about how hiring priorities have evolved, why traditional recruitment models are becoming less effective, and what businesses are looking for when building teams today.
To better understand what's driving this shift, we spoke with Artem Furs, Account Director at Gitmax, about how hiring priorities have evolved, why traditional recruitment models are becoming less effective, and what businesses are looking for when building teams today.
Artem Furs is a recruitment and HR consulting expert with over 15 years of experience
in talent acquisition and flexible staffing.
He has worked with global companies including Accenture, EY, Danone, and PepsiCo.
in talent acquisition and flexible staffing.
He has worked with global companies including Accenture, EY, Danone, and PepsiCo.
Artem Furs,
Account Director at Gitmax
Account Director at Gitmax
Over the past two to three years, hiring has become more pragmatic, shifting from long-term planning to immediate value creation. [1] Companies now favor candidates who can deliver results quickly.
We live in what Sergey Deryabin in 2022 called a “TACI”—Turbulent, Anxious, Chaotic, Incomprehensible—world. (After Jamais Cascio’s concept - BANI in 2016). For business, this means plansshift quickly, markets change unexpectedly, and job descriptions can become outdated before hiring is finished. [2] (There are many such cases, not just rare exceptions in 2026.)
Previously, companies valued candidates for long-term fit, hiring those 70-75% aligned and training the rest over time. [3] Now, rapid AI adoption and business change mean this pace is insufficient; companies urgently seek experts with proven practical experience, adaptability, communication, and integration skills to minimize onboarding time.
Education still matters, but it’s mostly a hygiene factor. It shows how a person thinks, structures problems, and learns.
The real differentiator is practical expertise: what they’ve solved, how quickly they grasp the business context,
and whether they deliver in a changing environment. [4]
We live in what Sergey Deryabin in 2022 called a “TACI”—Turbulent, Anxious, Chaotic, Incomprehensible—world. (After Jamais Cascio’s concept - BANI in 2016). For business, this means plansshift quickly, markets change unexpectedly, and job descriptions can become outdated before hiring is finished. [2] (There are many such cases, not just rare exceptions in 2026.)
Previously, companies valued candidates for long-term fit, hiring those 70-75% aligned and training the rest over time. [3] Now, rapid AI adoption and business change mean this pace is insufficient; companies urgently seek experts with proven practical experience, adaptability, communication, and integration skills to minimize onboarding time.
Education still matters, but it’s mostly a hygiene factor. It shows how a person thinks, structures problems, and learns.
The real differentiator is practical expertise: what they’ve solved, how quickly they grasp the business context,
and whether they deliver in a changing environment. [4]
– Over the past two years, how have hiring approaches changed, and why are traditional long-term hiring models becoming less effective for many businesses today?
Over the past two to three years, hiring has become more pragmatic, shifting from long-term planning
to immediate value creation. [1] Companies now
favor candidates who can deliver results quickly.
We live in what Sergey Deryabin in 2022 called a “TACI”—Turbulent, Anxious, Chaotic, Incomprehensible—world. (After Jamais Cascio’s concept - BANI in 2016). For business, this means plansshift quickly, markets change unexpectedly, and job descriptions can become outdated before hiring is finished. [2] (There are many such cases, not just rare
exceptions in 2026.)
Previously, companies valued candidates for long-term fit, hiring those 70-75% aligned and training
the rest over time. [3] Now, rapid AI adoption and business change mean this pace is insufficient; companies urgently seek experts with proven practical experience, adaptability, communication,
and integration skills to minimize onboarding time.
Education still matters, but it’s mostly a hygiene factor. It shows how a person thinks, structures problems, and learns. The real differentiator is practical expertise: what they’ve solved, how quickly they grasp the business context, and whether they deliver in a changing environment. [4]
to immediate value creation. [1] Companies now
favor candidates who can deliver results quickly.
We live in what Sergey Deryabin in 2022 called a “TACI”—Turbulent, Anxious, Chaotic, Incomprehensible—world. (After Jamais Cascio’s concept - BANI in 2016). For business, this means plansshift quickly, markets change unexpectedly, and job descriptions can become outdated before hiring is finished. [2] (There are many such cases, not just rare
exceptions in 2026.)
Previously, companies valued candidates for long-term fit, hiring those 70-75% aligned and training
the rest over time. [3] Now, rapid AI adoption and business change mean this pace is insufficient; companies urgently seek experts with proven practical experience, adaptability, communication,
and integration skills to minimize onboarding time.
Education still matters, but it’s mostly a hygiene factor. It shows how a person thinks, structures problems, and learns. The real differentiator is practical expertise: what they’ve solved, how quickly they grasp the business context, and whether they deliver in a changing environment. [4]
– Over the past two years, how have
hiring approaches changed, and why
are traditional long-term hiring models becoming less effective for many businesses today?
hiring approaches changed, and why
are traditional long-term hiring models becoming less effective for many businesses today?
Traditional hiring models are built on stability and predictability: fixed roles, long planning cycles, and clear
budgets. With business speed and market unpredictability rising, companies can no longer rely on these structures.
Even management consulting giants struggle, as long-term strategies provide decreasing value in today's
fast-changing context.
No doubt a permanent hire is still the right solution for core strategic roles. But for many projects, companies cannot afford to spend 2-4 months searching for the right person, then another few months onboarding them, only
to discover that the business's needs have changed. [5]
The central challenge is not just cost but the need for speed, flexibility, and reduced risk. Long-term hires force organizations into commitments that may not match fast-changing realities. Companies must now dynamically adjust teams, expertise, and directions in response to market volatility. This is why outstaffing and flexible staffing have become more attractive, enabling companies to access strong specialists quickly without turning every need into a permanent headcount decision.
budgets. With business speed and market unpredictability rising, companies can no longer rely on these structures.
Even management consulting giants struggle, as long-term strategies provide decreasing value in today's
fast-changing context.
No doubt a permanent hire is still the right solution for core strategic roles. But for many projects, companies cannot afford to spend 2-4 months searching for the right person, then another few months onboarding them, only
to discover that the business's needs have changed. [5]
The central challenge is not just cost but the need for speed, flexibility, and reduced risk. Long-term hires force organizations into commitments that may not match fast-changing realities. Companies must now dynamically adjust teams, expertise, and directions in response to market volatility. This is why outstaffing and flexible staffing have become more attractive, enabling companies to access strong specialists quickly without turning every need into a permanent headcount decision.
– Why are traditional long-term hiring models becoming less effective for many businesses today?
Traditional hiring models are built on stability
and predictability: fixed roles, long planning cycles, and clear budgets. With business speed and market unpredictability rising, companies can no longer rely on these structures. Even management consulting giants struggle, as long-term strategies provide decreasing value in today's fast-changing context.
No doubt a permanent hire is still the right solution
for core strategic roles. But for many projects, companies cannot afford to spend 2-4 months searching for the right person, then another few months onboarding them, only to discover that
the business's needs have changed. [5]
The central challenge is not just cost but the need
for speed, flexibility, and reduced risk. Long-term hires force organizations into commitments that may not match fast-changing realities. Companies must now dynamically adjust teams, expertise, and directions in response to market volatility. This is why outstaffing and flexible staffing have become more attractive, enabling companies to access strong specialists quickly without turning every need into
a permanent headcount decision.
and predictability: fixed roles, long planning cycles, and clear budgets. With business speed and market unpredictability rising, companies can no longer rely on these structures. Even management consulting giants struggle, as long-term strategies provide decreasing value in today's fast-changing context.
No doubt a permanent hire is still the right solution
for core strategic roles. But for many projects, companies cannot afford to spend 2-4 months searching for the right person, then another few months onboarding them, only to discover that
the business's needs have changed. [5]
The central challenge is not just cost but the need
for speed, flexibility, and reduced risk. Long-term hires force organizations into commitments that may not match fast-changing realities. Companies must now dynamically adjust teams, expertise, and directions in response to market volatility. This is why outstaffing and flexible staffing have become more attractive, enabling companies to access strong specialists quickly without turning every need into
a permanent headcount decision.
– Why are traditional long-term hiring models becoming less effective
for many businesses today?
for many businesses today?
Well, it’s going to sound banal, but AI has fundamentally changed perspectives on both productivity and talent. It enables teams to move faster but adds uncertainty as businesses reevaluate what should be automated, which roles will evolve, and what new skills are essential, even when the actual capabilities of teams remain unclear.
So businesses avoid building large teams based on assumptions that might change in six months.
Instead, they prefer flexible experts to help with testing, implementation, and adaptation.
AI has also changed company expectations for specialists. Now, beyond technical abilities, such as coding, infrastructure management, data analysis, and product development, experts are expected to leverage AI tools to enhance speed, quality, and decision-making. The most valued professionals are those who integrate AI into their daily work to drive results efficiently.
As previously noted, companies seek multifunctional experts [6] who are good team communicators, have deep technical expertise, and understand AI: much like having a driver's license or being an advanced Excel user [7]
was essential on CVs five years ago. Companies want access to people with very specific and up-to-date expertise,
like AI engineers, data specialists, DevOps, cybersecurity experts, product-minded developers - without always
creating a permanent role from day one.
So businesses avoid building large teams based on assumptions that might change in six months.
Instead, they prefer flexible experts to help with testing, implementation, and adaptation.
AI has also changed company expectations for specialists. Now, beyond technical abilities, such as coding, infrastructure management, data analysis, and product development, experts are expected to leverage AI tools to enhance speed, quality, and decision-making. The most valued professionals are those who integrate AI into their daily work to drive results efficiently.
As previously noted, companies seek multifunctional experts [6] who are good team communicators, have deep technical expertise, and understand AI: much like having a driver's license or being an advanced Excel user [7]
was essential on CVs five years ago. Companies want access to people with very specific and up-to-date expertise,
like AI engineers, data specialists, DevOps, cybersecurity experts, product-minded developers - without always
creating a permanent role from day one.
– What role has AI played in accelerating the move toward flexible staffing models?
Well, it’s going to sound banal, but AI has fundamentally changed perspectives on both productivity and talent. It enables teams to move faster but adds uncertainty as businesses reevaluate what should be automated, which roles will evolve, and what new skills are essential, even when the actual capabilities of teams remain unclear.
So businesses avoid building large teams based on assumptions that might change in six months. Instead, they prefer flexible experts to help with testing, implementation, and adaptation.
AI has also changed company expectations for specialists. Now, beyond technical abilities, such
as coding, infrastructure management, data analysis, and product development, experts are expected
to leverage AI tools to enhance speed, quality, and decision-making. The most valued professionals are those who integrate AI into their daily work to drive results efficiently.
As previously noted, companies seek multifunctional experts [6] who are good team communicators, have deep technical expertise, and understand AI: much like having a driver's license or being an advanced Excel user [7] was essential on CVs five years ago. Companies want access to people with very specific and up-to-date expertise, like AI engineers, data specialists, DevOps, cybersecurity experts, product-minded developers - without always creating
a permanent role from day one.
So businesses avoid building large teams based on assumptions that might change in six months. Instead, they prefer flexible experts to help with testing, implementation, and adaptation.
AI has also changed company expectations for specialists. Now, beyond technical abilities, such
as coding, infrastructure management, data analysis, and product development, experts are expected
to leverage AI tools to enhance speed, quality, and decision-making. The most valued professionals are those who integrate AI into their daily work to drive results efficiently.
As previously noted, companies seek multifunctional experts [6] who are good team communicators, have deep technical expertise, and understand AI: much like having a driver's license or being an advanced Excel user [7] was essential on CVs five years ago. Companies want access to people with very specific and up-to-date expertise, like AI engineers, data specialists, DevOps, cybersecurity experts, product-minded developers - without always creating
a permanent role from day one.
– What role has AI played in accelerating the move toward flexible staffing models?
I would say yes, definitely. We see more companies thinking in terms of outcomes, becoming more and more
result-oriented. They focus on something like a product launch, migrating infrastructure, improving system
performance, building an AI feature, closing a technical gap, supporting a new market, or stabilizing delivery.
This has led companies to rethink hiring: instead of asking, “Who should we hire permanently on this FTE?”
they increasingly ask, “What result is needed, and which expertise gets us there fastest?” [8]
That is a very different mindset. It means businesses are becoming more open-minded to mixed workforce
models; for instance, core internal teams, external experts, outstaffed engineers, contractors, and specialized
partners working together.
Of course, no one speaks of internal hiring as a replacement, but rather as a supplement. A company may keep product ownership and key architecture in-house while bringing in external specialists to accelerate results, cover rare expertise, or support a temporary increase in workload.
result-oriented. They focus on something like a product launch, migrating infrastructure, improving system
performance, building an AI feature, closing a technical gap, supporting a new market, or stabilizing delivery.
This has led companies to rethink hiring: instead of asking, “Who should we hire permanently on this FTE?”
they increasingly ask, “What result is needed, and which expertise gets us there fastest?” [8]
That is a very different mindset. It means businesses are becoming more open-minded to mixed workforce
models; for instance, core internal teams, external experts, outstaffed engineers, contractors, and specialized
partners working together.
Of course, no one speaks of internal hiring as a replacement, but rather as a supplement. A company may keep product ownership and key architecture in-house while bringing in external specialists to accelerate results, cover rare expertise, or support a temporary increase in workload.
– Are companies increasingly hiring for projects and outcomes rather than traditional fixed roles?
I would say yes, definitely. We see more companies thinking in terms of outcomes, becoming more and more result-oriented. They focus on something like
a product launch, migrating infrastructure, improving system performance, building an AI feature, closing
a technical gap, supporting a new market, or stabilizing delivery.
This has led companies to rethink hiring: instead
of asking, “Who should we hire permanently on this FTE?” they increasingly ask, “What result is needed, and which expertise gets us there fastest?” [8]
That is a very different mindset. It means businesses are becoming more open-minded to mixed workforce models; for instance, core internal teams, external experts, outstaffed engineers, contractors, and specialized partners working together.
Of course, no one speaks of internal hiring as
a replacement, but rather as a supplement.
A company may keep product ownership and key architecture in-house while bringing in external specialists to accelerate results, cover rare expertise, or support a temporary increase in workload.
a product launch, migrating infrastructure, improving system performance, building an AI feature, closing
a technical gap, supporting a new market, or stabilizing delivery.
This has led companies to rethink hiring: instead
of asking, “Who should we hire permanently on this FTE?” they increasingly ask, “What result is needed, and which expertise gets us there fastest?” [8]
That is a very different mindset. It means businesses are becoming more open-minded to mixed workforce models; for instance, core internal teams, external experts, outstaffed engineers, contractors, and specialized partners working together.
Of course, no one speaks of internal hiring as
a replacement, but rather as a supplement.
A company may keep product ownership and key architecture in-house while bringing in external specialists to accelerate results, cover rare expertise, or support a temporary increase in workload.
– Are companies increasingly hiring
for projects and outcomes rather
than traditional fixed roles?
for projects and outcomes rather
than traditional fixed roles?
The way companies approach hiring is undergoing a fundamental shift. Rather than planning years ahead,
businesses are increasingly prioritizing speed, adaptability, and access to the expertise
they need right now.
As Artem explains, this doesn't mean permanent hiring is disappearing. Instead, organizations are becoming more intentional about when to build internal capabilities and when to bring in specialized expertise to move faster and respond to change.
businesses are increasingly prioritizing speed, adaptability, and access to the expertise
they need right now.
As Artem explains, this doesn't mean permanent hiring is disappearing. Instead, organizations are becoming more intentional about when to build internal capabilities and when to bring in specialized expertise to move faster and respond to change.
[1] Deloitte 2026 Global Human Capital Trends: 7 out of 10 business leaders say their primary competitive strategy for the next three years is to become faster and more agile. The report also notes that long planning cycles and predictable execution are no longer sufficient in today's business environment.
[2] Deloitte 2026 Global Human Capital Trends: Deloitte argues that markets, technologies, and stakeholder expectations shift in real time, making the ability to sense change, experiment rapidly, and continuously adapt a core competitive advantage.
[3] Based on field observations
[4] Research on skill-based hiring: Analysis of AI roles in the UK shows that employers are increasingly removing university degree requirements, while AI skills continue to command a significant wage premium.
[5] Based on Gitmax's experience recruiting senior and specialized talent.
[6] PwC 2026 Global AI Jobs Barometer: AI-exposed junior roles are seven times more likely to require traditionally senior capabilities such as leadership. Rather than replacing human judgment, AI is increasing demand for leadership, decision-making, and other high-value skills.
[7] LinkedIn Work Change Report: By 2030, 70% of the skills used in most jobs are expected to change. Since 2022, the rate at which professionals add new skills to their LinkedIn profiles has increased by 140%, underscoring the growing importance of continuous upskilling.
[8] Deloitte – Skills-Based Organization: Deloitte argues that organizations are shifting from making workforce decisions based on job titles to making them based on skills. Traditional job structures are becoming less effective as the primary way to organize work and talent.
[2] Deloitte 2026 Global Human Capital Trends: Deloitte argues that markets, technologies, and stakeholder expectations shift in real time, making the ability to sense change, experiment rapidly, and continuously adapt a core competitive advantage.
[3] Based on field observations
[4] Research on skill-based hiring: Analysis of AI roles in the UK shows that employers are increasingly removing university degree requirements, while AI skills continue to command a significant wage premium.
[5] Based on Gitmax's experience recruiting senior and specialized talent.
[6] PwC 2026 Global AI Jobs Barometer: AI-exposed junior roles are seven times more likely to require traditionally senior capabilities such as leadership. Rather than replacing human judgment, AI is increasing demand for leadership, decision-making, and other high-value skills.
[7] LinkedIn Work Change Report: By 2030, 70% of the skills used in most jobs are expected to change. Since 2022, the rate at which professionals add new skills to their LinkedIn profiles has increased by 140%, underscoring the growing importance of continuous upskilling.
[8] Deloitte – Skills-Based Organization: Deloitte argues that organizations are shifting from making workforce decisions based on job titles to making them based on skills. Traditional job structures are becoming less effective as the primary way to organize work and talent.
In Part 2, we'll dive deeper into the practical side of flexible staffing; examining the advantages it offers beyond cost savings, the misconceptions businesses still have about outstaffing, and how workforce models are likely to evolve over the next three to five years.
In Part 2, we'll dive deeper into
the practical side of flexible
staffing; examining the advantages
it offers beyond cost savings,
the misconceptions businesses
still have about outstaffing, and how workforce models are likely to evolve over the next three to five years.
the practical side of flexible
staffing; examining the advantages
it offers beyond cost savings,
the misconceptions businesses
still have about outstaffing, and how workforce models are likely to evolve over the next three to five years.
Agile Development
- For instance, when a tech startup needs to release a minimum viable product (MVP) quickly to test the market, Agile is often the preferred methodology. It allows the development team to release functional software in short cycles, gather user feedback, and make rapid improvements — much like an athlete honing their performance with each training session.
Waterfall Development
- Waterfall is often used in large-scale projects where requirements are well understood from the beginning and where changes midstream could lead to costly delays. Think of industries like aerospace or government contracting, where thorough documentation and adherence to strict guidelines are crucial. Just as a marathoner prepares meticulously for every mile, Waterfall teams spend significant time in the planning stages to ensure smooth execution.