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Top tech trends to watch for in 2018

Top tech trends to watch for in 2018

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Tharika Tellicherry
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January 29, 2018
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3 min read
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“We didn’t do anything wrong, but somehow, we lost,” said Nokia’s CEO Stephen Elop in his speech soon after Nokia’s announcement of being acquired by Microsoft in September 2013. The mobile giant that was once valued at $222 billion at its peak was acquired for just $7.2 billion by Microsoft that year. Failure to adapt to new trends in smartphone technology drove the legendary mobile company from market domination to sell-off.

The biggest lesson for from Nokia’s collapse in the mobile industry is to adapt to new tech trends before your consumers abandon you. Fast innovation is the key to keeping up with new technologies. By discerning the latest trends, companies can leverage the right technology and adapt in time to succeed. Here are the top tech trends that will define the IT landscape in 2018:

1) The incredible AI

Artificial intelligence (AI) is going to get better and smarter in 2018. Thanks to artificial intelligence, your everyday appliances from the security system to entertainment console will become more automated and smarter. Using software algorithms and sensors, artificial intelligence based devices will be able to do more complex actions and will play a significant role in several domains including healthcare, smart cars, and personal security. From making the financial sector more accurate and secure to powering smart personal assistants like Siri, you will see more of artificial intelligence based technology in your everyday life.

2) Planet of the robots

With more research and investment in robotics, you will also see more of intelligent drones and robots in 2018. According to IDC’s FutureScape: Worldwide Robotics 2017 Predictions report, 45% of the 200 leading global e-commerce and omnichannel commerce companies will deploy robotics systems in their order fulfillment, warehousing, and delivery operations. 2018 is going to witness the emergence of robotics in fields including agriculture, manufacturing, and medicine. Lifelike robots like Sophia could even play the role of human companions and help take care of children, the elderly and people with special needs. Sophia who looks like the late actor Audrey Hepburn was even awarded full citizenship of Saudi Arabia. Those worried about a robotic invasion can put their fears to rest. Robotics of the future will be designed to help people achieve more.

3) Mixed reality: The rise of immersive experience

With the digital revolution, today we have access to more content than ever before. Earlier, augmented reality (AR) and virtual reality (VR) defined the way people interacted with the digital world. The coming days will see the emergence of mixed reality (MR) that combines both augmented reality and virtual reality. The mixed reality technology enables users to interact in an environment where both physical and digital objects co-exist. 2018 will witness more application of the mixed reality technology in fields ranging from simulation-based learning, military training, aviation, healthcare to interactive product content management. According to the research firm Reportbuyer.com, the global mixed reality market size is expected to touch $2.8 billion by 2023.

4) Blockchain: The force awakens

The blockchain is the fundamental technology behind cryptocurrencies like bitcoin. The exponential rise of bitcoins has rekindled everyone’s interest in blockchain technology. The technology provides a secure way of sharing encrypted data on anything, from money to medical records, between companies, people, and institutions. Blockchain has the potential to revolutionize the financial sector and the world economy. In 2018, companies are going to invest heavily in developing their blockchain and fintech capabilities. As we move toward a digital, technologically advanced financial world, blockchain will play a crucial role in making our financial systems faster, more secure and efficient.

5) The age of machine learning

Businesses will increasingly leverage on machine learning to gain a competitive advantage in 2018. Machine learning deals with the technology that enables computers to learn explicitly without being programmed. The technology can be used to analyze large volumes of data and predict patterns. In the coming days, machine learning will be widely used in fields including data security, personal security, financial trading, healthcare, personalized marketing and online search.

6) IoT: Unchained

IoT is here to stay and thrive. According to Business Insider, the business spends on IoT solutions will reach $6 trillion by 2021. Internet of Things (IoT) is a network of devices that is embedded with software and sensors that enable these devices to connect and exchange data. The technology is applied in verticals including wearables, connected cars, connected homes, connected cities and industrial internet. 2018 will see the rise of “digital twins,” the next step in IoT-based technology. Companies will rely on the technology to predict problems through data analysis and simulations. Another disruptive technology that will emerge will be based on a combination of IoT and Blockchain technologies. The technology will be applied in domains including warehousing, healthcare, and financial sectors. There will be connected devices everywhere.

As the waves of new and emerging technologies hit the world, it is a good idea to start learning more about these new and upcoming tech domains. In today’s high-tech era, leveraging the right technology can mean the difference between success and failure. Consumers are quick to punish those who don’t innovate fast.

Nokia did not do anything wrong except miss out on the latest trends in mobile technology. While the competitors quickly caught on the demand for smarter phones, Nokia was left far behind. In the end, it is the lack of innovation and the failure to adapt to emerging technologies that force companies out of business. The lesson for everyone is to adapt and innovate before it is too late.

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Author
Tharika Tellicherry
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January 29, 2018
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3 min read
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What AI Is Forcing HR to Rethink About Hiring

What AI is forcing HR to rethink

For recruiters and talent leaders, AI has made one thing clear: resumes can no longer be trusted as the primary signal of candidate capability. What AI is forcing HR to rethink is the entire screening stack — from how reqs are written, to how the ATS filters applicants, to how quality of hire (QoH) is measured against time-to-fill. According to LinkedIn's Future of Recruiting 2024 report, 73% of recruiters say skills-based hiring is a priority, yet most pipelines still screen on degree and employer brand at the ATS layer. That gap is where the rethink begins.

Why traditional resumes no longer predict strong hires

Resumes measure presentation more reliably than capability. Recruiters have long used job titles, company names, degrees, and years of experience as proxies for performance, but generative AI tools — ChatGPT, Teal, Rezi, and Kickresume among them — have collapsed the cost of producing a polished application. The World Economic Forum's Future of Jobs Report 2023 found that 44% of workers' core skills are expected to change by 2027, which means a resume snapshot ages faster than the role it describes.

For recruiters, the operational impact is direct: pipelines fill, screen rates rise, and yet QoH stays flat. As AI becomes more deeply embedded in hiring, HR leaders are being forced to rethink a single question:

What if resumes are no longer the best predictor of performance?

That question is reshaping recruitment faster than many organizations expected — though, as discussed later, the shift away from resumes carries its own trade-offs.

Share of Workers' Core Skills Expected to Change by 2027
Source: World Economic Forum Future of Jobs Report 2023

The resume was built for a different era

Modern work no longer fits the resume's static format. Skills evolve in months rather than years, roles overlap across functions, and professionals build expertise through online communities, freelance projects, bootcamps, and self-directed learning. According to SHRM's 2024 Talent Trends research, nearly half of HR leaders report that candidates from non-traditional backgrounds are increasingly competitive on assessments.

Resumes still reduce people to standardized timelines, and many capable candidates are filtered out by ATS rules simply because they lack the "right" employer logos. At the same time, candidates skilled in resume optimization can outperform genuinely capable professionals at the screen stage — a pattern that pre-dates AI but has been amplified by it.

It has become far easier for candidates to generate polished resumes, cover letters, and interview responses in minutes. For recruiters, the takeaway is practical: formatting and phrasing are no longer reliable proxies for capability.

AI did not break hiring — it exposed existing problems

AI did not create the resume problem; it surfaced one already present in most hiring funnels. Surveys of recruiters, including Gartner's 2024 HR research, have consistently shown three pre-AI pressures: recruiters overwhelmed by application volume, candidates optimizing resumes to pass ATS filters, and hiring managers reporting weak outcomes despite reviewing seemingly strong resumes.

AI accelerated these problems to a point where they can no longer be ignored. Many candidates can now generate a highly optimized application in seconds, and recruiters increasingly struggle to distinguish between candidates skilled at self-presentation and those who can actually do the work.

The operational shift is moving from:

"What does your resume say?"

Toward:

"Can you actually do the job?"

The rise of skills-based hiring

Skills-based hiring outperforms resume screening because it measures demonstrated capability rather than credential proximity. A growing number of organizations — including IBM, Accenture, and Delta, profiled in LinkedIn's Skills Path program — are moving toward skills-first models that prioritize practical assessments, simulations, project work, and role-specific problem-solving over employer brand or degree.

This trend is most visible in technology hiring, where coding assessments and real-world technical evaluations generally provide stronger signals than resumes alone, particularly when compared against resume-only screens for time-to-productivity. HackerEarth has run over 100 million developer assessments across enterprise hiring programs, and the consistent pattern in that dataset is that demonstrated coding performance correlates more closely with on-the-job output than degree or prior employer.

Beyond tech, a growing number of organizations are extending the model: marketing teams using campaign-brief exercises, sales teams using recorded customer-handling scenarios, and operations teams using situational judgment tests. For a deeper view of how this maps to specific roles, see our skills-based hiring guide and developer assessment platform.

Where skills-based hiring breaks down

Skills-based hiring is not without trade-offs, and recruiters evaluating it should plan for known failure modes:

  • Assessment bias. Poorly designed assessments can disadvantage career returners, caregivers, and candidates with limited test-taking time as severely as resume screens disadvantage non-traditional backgrounds.
  • Gaming of take-home tests. Unproctored coding or case exercises are increasingly solvable with generative AI, which means assessment design has to evolve in step with candidate tooling.
  • Candidate experience at scale. Long assessment batteries lower completion rates and damage employer brand, particularly for senior candidates who have multiple offers in play.
  • Legal exposure. In jurisdictions including New York City (Local Law 144) and under the EU AI Act, automated employment decision tools are subject to bias audits and disclosure requirements. Recruiters should confirm vendor compliance before deploying AI-driven scoring.

The honest read: most organizations announcing a "shift" to skills-based hiring still filter by degree at the ATS layer. The shift is real, but it is uneven.

Skills-Based Hiring Priority vs. ATS Screening Reality
Source: LinkedIn Future of Recruiting 2024; ATS screening figure illustrative based on article claims

Why HR leaders are rethinking potential

Potential is becoming more measurable in ways resumes never allowed. Traditional hiring often prioritized pedigree — familiar universities, recognizable employers, conventional career paths — but AI-powered assessment platforms (HackerEarth, HireVue, Pymetrics, Codility, and Workday Skills Cloud among them) score candidates on demonstrated performance against role-specific tasks, calibrated to a benchmark population.

These tools typically combine task-based evaluations, behavioral simulations, and structured scoring rubrics. Their limits matter too: they score what they are trained to score, they can encode bias from the training population, and they do not measure long-arc traits like cultural contribution or leadership trajectory. Recruiters should treat them as one signal in a structured interview loop, not a single decision point.

Research suggests that candidates without elite degrees frequently match or outperform credentialed peers on standardized technical assessments. In many cases, career switchers and self-taught professionals demonstrate strong adaptability and practical skill. Organizations that shift toward capability-based evaluation may gain access to broader and more diverse talent pools — though, as noted above, only if assessment design itself is audited for fairness.

The recruiter's role is changing

AI is not replacing recruiters; it is shifting where recruiters spend their time. Traditional recruitment rewarded screening volume and speed. Modern hiring increasingly rewards judgment, stakeholder alignment, and structured decision-making.

As automation handles sourcing, scheduling, resume parsing, and initial outreach, recruiters are spending more time on work AI cannot do well:

  • Probing candidate motivation through structured behavioral interviews
  • Evaluating adaptability against specific role demands using scorecards
  • Building hiring-manager alignment on the req and intake brief
  • Designing candidate-experience touchpoints that protect offer-accept rates
  • Calibrating assessment results against on-the-job performance data

The recruiter who succeeds in an AI-heavy pipeline is the one who can interpret signal, not the one who can scan resumes faster.

Candidates are changing faster than hiring systems

Modern career paths now move faster than most ATS configurations. Today's workforce values flexibility, creativity, continuous learning, and project-based growth, and many professionals build experience through freelance work, startups, creator platforms, and side projects. Their resumes often look unconventional, but unconventional no longer equates to unqualified.

Organizations that shift toward capability-based evaluation may access talent pools that rigid resume filters would otherwise miss. For practical guidance on adjusting screening criteria, see our guide to evaluating an ATS for skills-based hiring.

The future of hiring will feel more human

There is an irony in the AI shift: as resumes become easier to automate, organizations are being pushed to evaluate creativity, adaptability, collaboration, and real-world problem-solving more directly. The likely structure of mature AI-enabled hiring is AI handling repetitive tasks — sourcing, scheduling, parsing, initial scoring — while recruiters and hiring managers focus on nuance, context, and long-term fit.

FAQ

Is skills-based hiring more effective than resume screening? Skills-based hiring tends to predict on-the-job performance more reliably than resume screening for roles where the work can be assessed directly, such as engineering, data, sales, and marketing execution. According to LinkedIn's Future of Recruiting report, 73% of recruiters now prioritize skills-based approaches. Effectiveness depends heavily on assessment design and on whether downstream ATS filters still gate candidates by degree.

What HR processes is AI changing first? AI is changing sourcing, resume parsing, candidate matching, and initial assessment scoring first, because these are high-volume, rules-based tasks. Structured interviewing, offer negotiation, and onboarding remain primarily human-led, though AI-assisted note-taking and scorecard analysis are growing.

Will AI replace recruiters? AI is unlikely to replace recruiters, but it is changing the skill profile. Recruiters who can interpret assessment data, align hiring managers, and design candidate experience will be more valuable; recruiters whose role is primarily resume scanning are most exposed.

How do I evaluate an AI hiring tool for bias? Ask the vendor for a bias audit report (required under NYC Local Law 144 for automated employment decision tools), the demographic composition of the training data, the validation methodology against job performance, and the appeal process for candidates. Avoid tools that cannot answer all four.

Is resume-based hiring going away? Resume-based hiring is under pressure but not disappearing. Most organizations are moving toward hybrid models where resumes provide context and assessments provide the capability signal. A full move away from resumes is unlikely in the next hiring cycle for most enterprises.

What is the biggest risk of switching to skills-based hiring? The biggest risk is poorly designed assessments that introduce new forms of bias or damage candidate experience. A skills-based process built on a long, unproctored, untested assessment battery will perform worse than a structured resume screen.

Next steps: See it in action

If you are a recruiter or talent leader evaluating how to move from resume-led to skills-led screening, book a demo of HackerEarth Assessments to see how role-specific evaluations, proctoring, and benchmarked scoring fit into an existing ATS pipeline. For background reading, see our developer assessment platform overview and the HackerEarth recruiter blog.

Recruiters who pair structured assessment data with strong human judgment build better pipelines than either resumes or AI alone can produce.

Recruitment Questions Every HR Professional Should Know

Recruitment Questions Every HR Professional Should Know

Why Modern Hiring Fails When Questions Stay Outdated

Recruitment today is no longer just about verifying experience or matching keywords on a resume. Candidates are more prepared, interviews are more structured, and expectations on both sides are significantly higher.

Yet many hiring conversations still rely on outdated or surface-level questions. The result is predictable — polished answers, unclear signals, and decisions made on incomplete understanding.

In a market where talent moves fast and culture fit matters more than ever, the quality of questions defines the quality of hiring outcomes.

From “Tell Me About Yourself” to Understanding Real Intent

Traditional opening questions often fail to reveal anything meaningful about a candidate’s intent or direction.

Modern HR conversations are shifting toward understanding why a candidate is making a move at this specific point in their career, and what kind of work actually keeps them engaged beyond compensation.

This matters because today’s workforce is not driven by job stability alone. They are driven by alignment, learning curves, and perceived growth momentum.

If this layer is missed early in the interview, the rest of the evaluation becomes less reliable.

Moving Beyond Scripted Answers in Interviews

One of the biggest challenges HR teams face today is not lack of talent, but over-prepared talent.

With access to AI tools, interview guides, and curated responses, candidates often enter interviews with highly refined narratives. While this improves communication, it also reduces signal clarity for recruiters.

This is why HR professionals are increasingly focusing on questions that cannot be easily rehearsed — questions that explore decision-making logic, trade-offs, and real-time thinking patterns rather than memorized stories.

The goal is no longer to hear “what happened,” but to understand “how a candidate processes what happens.”

Evaluating Behavioral Depth Instead of Surface Fit

Cultural fit is often misunderstood as shared interests or personality alignment. In modern hiring, it is more about behavioral consistency within a work environment.

HR teams are now expected to identify how a candidate reacts under ambiguity, responds to feedback loops, and adapts when expectations shift mid-execution.

This shift is important because modern roles are rarely static. Priorities change quickly, teams evolve constantly, and execution environments are rarely predictable.

Candidates who can remain stable in dynamic conditions are increasingly more valuable than those who only perform well in structured settings.

Identifying Ownership Mindset Over Task Execution

Task completion alone is no longer a strong hiring indicator.

What HR teams are prioritizing now is the ownership mindset — how a candidate behaves when outcomes are unclear, accountability is shared, or success metrics evolve during execution.

This is where advanced questioning becomes critical. It helps distinguish between candidates who simply execute instructions and those who actively engage with outcomes.

In fast-moving organizations, this difference directly impacts productivity, team reliability, and leadership pipeline strength.

Assessing Adaptability in a Rapidly Changing Work Environment

Workplaces today are defined by continuous change — shifting priorities, evolving tools, and hybrid collaboration models.

Because of this, adaptability has become a core hiring parameter rather than a soft skill.

HR professionals are increasingly focusing on understanding how quickly a candidate can recalibrate when expectations shift, how they handle uncertainty, and how they operate without complete information.

This is especially relevant in roles where ambiguity is the default state rather than the exception.

Rethinking What “Good Answers” Actually Mean

In traditional interviews, clarity and confidence were often equated with strong performance.

However, modern hiring has started to challenge this assumption.

Well-structured, confident answers do not always reflect real capability, especially in environments where responses may be influenced by preparation tools or rehearsed narratives.

Instead, HR teams are placing higher value on depth, consistency, and reasoning quality — even if responses are less polished.

The focus is shifting from presentation to thinking patterns.

Final Thoughts

Recruitment is evolving from a question-and-answer process into a deeper evaluation of mindset, adaptability, and decision-making behavior.

For HR and talent acquisition teams, the challenge is no longer just identifying qualified candidates. It is identifying candidates whose thinking style aligns with modern, fast-changing work environments.

In this context, better hiring outcomes are not driven by more interviews or more resumes.

They are driven by better questions that reveal how candidates actually think, not just how well they respond.

Why Empathy Could Be Your Biggest Hiring Advantage

Why Empathy Could Be Your Biggest Hiring Advantage

Why Human-Centered Hiring Matters More Than Ever

Hiring has never been more optimized than it is today.

From AI-powered recruitment tools to automated screening systems and structured interview workflows, HR and talent acquisition teams now have more ways than ever to improve hiring speed, consistency, and scalability.

But in the middle of this efficiency-driven approach, one critical element is slowly disappearing: employee empathy.

Empathy in hiring is not about slowing down recruitment or making decisions less objective. It is about ensuring candidates are treated like people navigating important career decisions, not just profiles moving through a hiring pipeline.

As recruitment becomes increasingly system-driven, preserving the human side of hiring is becoming both more difficult and more important.

For HR leaders and talent acquisition professionals, this is no longer just a workplace culture discussion. It directly impacts candidate experience, employer branding, hiring quality, and long-term employee retention.

When Hiring Feels Like a Process Instead of an Experience

Most modern recruitment systems are designed around efficiency.

Applications are filtered automatically, interviews are scheduled faster, and candidates move through hiring stages with minimal manual effort. Operationally, this creates speed and structure.

But from a candidate’s perspective, the experience can often feel distant and impersonal.

Many candidates go through multiple interview rounds without clear communication, feedback, or transparency about timelines and expectations. Even when the hiring process is fair, it may still feel mechanical.

This creates a growing challenge for HR and TA teams:

How do you maintain hiring efficiency without removing the human connection from recruitment?

That is where empathy becomes essential.

The Hidden Cost of Low-Empathy Hiring

The impact of low-empathy hiring is not always immediate, but it compounds over time.

Candidates remember how organizations made them feel during the recruitment process, especially during rejection or delayed communication. Those experiences shape employer perception long before someone becomes an employee.

Over time, this directly affects employer brand and candidate trust.

There is also another hidden cost.

When hiring becomes too rigid or overly process-driven, recruiters may overlook candidates with strong long-term potential simply because they do not perfectly match predefined criteria.

Without empathy, context disappears.

And when context disappears, opportunities are often missed.

For HR leaders, empathy is no longer just a soft skill. It is becoming a competitive hiring advantage.

Why Empathy Is Becoming a Competitive Hiring Skill

Today’s workforce is far more dynamic than it was a decade ago.

Professionals switch industries, build careers through unconventional paths, and learn skills outside traditional education systems. As a result, resumes and structured evaluations only tell part of the story.

Empathy helps recruiters understand what exists beyond the surface.

It allows hiring teams to better understand:

  • Career transitions
  • Employment gaps
  • Nontraditional experience
  • Personal growth journeys

This shift changes the entire hiring mindset.

Instead of asking:

“Does this candidate perfectly match the role?”

Recruiters are increasingly asking:

“What could this candidate become in the right environment?”

That perspective creates stronger and more future-focused hiring decisions.

Where Empathy Fits in Modern Recruitment

Empathy does not replace structured hiring systems.

In fact, it becomes most effective when built into them.

Simple improvements in communication can significantly improve candidate experience. Clear updates, transparent timelines, respectful rejection emails, and honest feedback all contribute to a more human-centered recruitment process.

These small changes often have a lasting impact on how candidates perceive an organization.

For HR teams, the goal is not to remove structure from hiring.

The goal is to ensure structure does not remove humanity.

Better Hiring Decisions Start With Better Human Understanding

Empathy also improves the quality of hiring decisions themselves.

When recruiters take time to understand a candidate’s context, they often uncover strengths that are not immediately visible on resumes or scorecards.

A candidate who appears average on paper may demonstrate exceptional adaptability, resilience, or problem-solving ability in real-world situations.

Without empathy, those signals are easy to miss.

For talent acquisition leaders, this means recognizing that hiring is not just about selecting the strongest profile.

It is about identifying the strongest long-term fit within a real human context.

Final Thoughts

As recruitment continues evolving through automation, AI hiring tools, and structured decision-making, the biggest risk is not losing efficiency.

It is losing humanity.

Employee empathy ensures hiring remains people-focused, even as processes become more technology-driven.

It does not slow recruitment down. Instead, it helps organizations create better candidate experiences, stronger employer brands, and more thoughtful hiring decisions.

Because candidates may forget interview questions or assessment scores.

But they will always remember how they were treated during the hiring process.

And in today’s competitive talent market, that experience often determines whether top talent chooses to join or walk away.

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