5 HR Tech Trends Shaping Your Business | Featured Image

5 HR Tech Trends Shaping Your Business

5 HR Tech Trends Shaping Your Business | Main Image

Technology continues to drive and disrupt today’s talent management strategies. As we move closer to the halfway point of 2017, we take a look at 5 key HR tech trends shaping your business.

Cybersecurity skills challenges

The widely publicised global data breach that affected the NHS last month highlights the very real risks to all businesses. After the talent shortage, PWC notes that cybersecurity is the second highest ranked concern for CEOs, with three quarters (76%) citing this it as a significant challenge in its annual CEO Survey. A UK government report also found that half of all businesses have experienced at least one data breach or cybersecurity attack in the past year, rising to two thirds of medium and large businesses. Your ability to secure your data is an increasing issue and the pressure is on HR to source talent with vital cybersecurity skills. A report from Experis found that demand for cybersecurity professionals is at an all time high, echoing an earlier survey from Robert Half, Technology and Recruitment : The Landscape For 2017 which found that sourcing tech talent with cybersecurity skills was a priority for over half of all hiring managers this year.

The ongoing debate over AI

Predictions of a jobless world have thrown the debate over AI sharply into focus but AI and automation offer a number of benefits for hiring teams. Writing in the Harvard Business Review, Satya Ramaswamy describes ‘machine to machine’ transactions as the ‘low hanging fruit’ of AI rather than ‘people displacement’.

Elsewhere, Gartner predicts that by 2022 smart machines and robots could replace highly trained professionals in sectors including tech, medicine, law and financial services, transforming them into ‘high margin’ industries resembling utilities. But it stresses the benefit that AI brings in replacing repetitive, mundane tasks and offering more meaningful work. The key is to create the right blend of AI and human skills, which HR is ideally positioned for. Gartner suggests that a further benefit of AI is the alleviation of skills shortages in talent starved sectors.

A beneficial and immediate use of AI for HR is the automation of mundane and repetitive tasks in the recruitment cycle through HR technology, allow hiring teams to focus on creating the effective candidate and employee experience that their business urgently needs.

Chatbots in hiring

Today chatbots are emerging as an essential tech tool for high volume recruitment, engaging with candidates via messaging apps with the aim of creating a more interactive and engaging hiring process. The AA was one of the first brands to feature this smart technology and this year it is predicted that chatbot Stanley will interview 2.5 million candidates. As the skills shortage continues, the chatbot offers a more direct and effective way of engaging with sought after millennials or graduate talent. Chatbots are also predicted to make HR’s life easier through simple interactions via mobile devices for both candidates and employees.

Dark data

While still in the exploration stage, dark data can offer vital insights into talent sourcing. Up to 80% of the data created is ‘unstructured’ or ‘dark’ data found in, for example, e-mails, text messages, spreadsheets and pds. At present it is not usable in analytics but AI can be leveraged to organise it into a more usable form. Last month it emerged that Apple have acquired a machine learning based company to strengthen its own capabilities in the area of dark data. Deloitte’s Global Talent Trends report for 2017 reports that only 9% of businesses have a good understanding of the talent dimensions that drive performance. Dark data may help to illuminate those dimensions.

Moving to predictive analytics

It’s not a new or emerging HR tech trend but the transition to predictive analytics is one that HR must eventually (reluctantly?) make as the skills gap in the UK widens and the availability of qualified and digitally able candidates continues to fall. Applying people analytics improves hiring outcomes, reduces the level of early departures from your business and enables HR to begin to predict and plan for future hiring needs. The first step towards predictive analytics is for tech-averse hiring teams to relinquish manual recruitment systems in favour of HR technology and begin to understand the key metrics affecting your hiring process.

Advorto’s recruitment software provides workflow and structure across the entire hiring process, offering a dynamic database of candidates and analytics. Used by some of the world’s leading organisations, it provides a straightforward first step into AI, HR analytics and big data. Start your 30 day free trial today.


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Is AI Really A Threat To Jobs?

Artificial Intelligence | The HR Tech Weekly®

Has the future obliteration of jobs by automation been over-exaggerated? At the end of last year Bank of England Governor Mark Carney warned that up to 50% of UK jobs could be wiped out by automation. A recent report suggests that so far the AI-jobs apocalypse has yet to materialise.

Recent research from the Chartered Institute of Ergonomics and Human Factors (CIEHF) together with CV-Library found that two thirds of businesses had not yet witnessed job losses due to automation. Over a third believed that automation had actually increased the number of jobs available.

This is a view broadly supported by Deloitte. In 2015, it highlighted the benefits of automation and its ability to create better quality jobs by removing tedious and dull work which increases the potential for errors due to boredom and distractions. Its research also noted that as a result of automation:

  • 3.5 million low risk jobs have been created since 2001, compared to 800,000 high risk jobs lost.
  • Each new low-risk job pays a salary £10,000 higher than the high risk job it replaced.

This does not alleviate concerns over automation. The CIPD’s Employee Outlook Survey also notes that nearly a quarter of employees are concerned that their job – or parts of it – may be automated within the next five years. Similarly, PwC’s UK Economic Outlook predicts that 30% jobs in the UK are at risk from automation by the early 2030s. Like Deloitte, however, it notes that the nature of available jobs will change. Sectors at highest risk of job losses through automation include transport, manufacturing, and wholesale and retail. Education and health and social work and education are at the lowest risk of being replaced.

Ongoing resistance to AI

The CIEHF/CV Library survey reports a ‘resistance’ among employees to automation as employers are failing to communicate its benefits effectively and HR remains one of the most reluctant to positively embrace automation within talent management strategies. Deloitte’s 2017 Human Capital Trends Survey found that progress towards people analytics in the last year remains stubbornly slow. This is perhaps unsurprising as nearly half of recruitment professionals are still not using applicant tracking software in hiring processes.

HR must first acknowledge the advantages of automation in recruitment to communicate its benefits more effectively. In hiring processes, this means the automation of mundane procedures, including personalised e-mails to job applicants, effective, streamlined screening to reduce unconscious bias and insights into key hiring metrics that impact your ability to hire. It also enables hiring teams to create a more effective onboarding processes to improve retention of new hires.

But why is HR so reluctant to embrace technology?

An article in the Harvard Business Review suggests that the resistance to AI is twofold. To accept and take advantage of automation, consumers must trust both in the technology and in the business delivering the innovation. In recruitment that means HR must have confidence in the supplier of recruitment software and its ability to deliver benefits to its hiring process.

The article also highlights three key points which are essential to gaining that confidence:

Cognitive compatibility : In other words, make it easy to understand. The more complex the nature of the technology, the less likely consumers are to trust its ability achieve desired goals. For HR, that goal is to streamline hiring processes to ensure not only faster hiring but a better quality of hire.

Trialability : A trial of potential new technology helps to understand the benefits and reduce any reluctance to embrace technology.

Usability : To encourage buy-in among tech-resistant hiring teams, technology, especially HR software, must be easy to use.

Recruitment software aside, as companies continue to invest in technology it is vital to maintain employee buy-in and foster trust by investing in upskilling employees to equip them to use digital skills in the workplace. The UK faces a significant digital skills crisis in addition to a wider talent shortage but employers are failing to invest in the necessary training to equip employees with vital skills. Training and development is essential for businesses that wish to not only retain but to continue to attract talent to their brand. It will also go some way to overcoming ‘resistance’ to technology in the workplace.

Ethical concerns

Overcoming ethical concerns is an issue that HR must consider in the future.

The EU[1] has proposed the creation of a European agency to provide technical, ethical and regulatory advice on robotics and AI, including the consideration of a minimum income to compensate people replaced by robots and a ‘kill switch’ for malfunctioning AI systems. A similar concern was recently expressed by the International Bar Association which warned that AI could ultimately lead to the introduction of legislation for quotas of human workers in the future[2].

While the debate over the benefits of AI at work continues, there is no doubt about the struggle that employers face to hire and retain qualified candidates. HR software is HR’s first step towards embracing the benefits of automation and creating more effective talent management strategies.

[1] MEPs vote on robots' legal status - and if a kill switch is required

[2] Rise of robotics will upend laws and lead to human job quotas, study says

A version of this article first appeared on Advorto’s website.

 

What Does Dark Data Mean For HR?

What Does Dark Data Mean For HR?

Dark data is predicted to be one of the emerging tech trends for 2017. As businesses explore more ways to transform talent management processes and slowly move towards analytics, the swathes of information contained in dark data may prove to be the missing piece in the recruitment jigsaw.

Gartner defines dark data as the ‘information assets organisations collect, process and store during regular business activities, but generally fail to use for other purposes’. It is used, inactive information found in unexplored files including e-mails, messages, spreadsheets, pdfs, audio and video files. For many companies this data lies dormant and discarded but the insight it contains may inform and drive future talent management and hiring decisions.

Deloitte’s reportDark analytics: Illuminating opportunities hidden in unstructured data’ highlights the opportunities in dark data but warns that within three years’ time the sheer amount of data available may prove to be unmanageable. Veritas estimates the cost of managing ‘untamed’ data at up to $3.3 trillion per year collectively by 2020.

Dark data in hiring

Used effectively dark data can offer vital insights into talent sourcing and retention patterns. Data that is lost or ‘goes dark’ may disrupt hiring processes. It may be something as simple as the lost CV of a qualified candidate or a missing vital background check that extends your time to hire. Effective hiring processes require active, easily accessible data to reduce the amount of time employees spend duplicating or recreating information they can’t find.

In considering the potential use of dark data in your hiring processes, keep in mind the following:

Clarify your problem : Deloitte recommends identifying the problem you wish to address before delving into your dark, or unstructured, data and decide what data sources might help in resolving it. Focus questions on one specific area and ensure it is measurable and of value for your hiring process. Extracting samples from a selected data source will help to quickly indicate its potential value rather than attempting the impossible and time consuming task of pouring through an expanse of information. For example, a paper based onboarding system may contain invaluable insights into why new hires are leaving your business within the first six months of employment. Too broad an approach will be overwhelming.

Be aware of risks : Historical recruitment data that is not easily accessible or securely stored could expose your business to issues with data protection. Information on former employees for example may not be needed again but must be stored appropriately and securely. A formal policy relating to the storage of data during the hiring process is essential. Veritas found that that over 25% of employees store personal data in corporate resources which may infringe on data privacy or copyright rules. 20% of employees also use personal devices to store business data. That may be vital dark or unstructured data lost to HR.

Incorporate technology : Paper based or manual recruitment processes add to the expanse of dark data generated every day. Korn Ferry notes that less than half (48%) of businesses use applicant tracking software in recruitment. Without those systems or basic technology, dark data risks adding to inefficiencies in hiring processes rather than offering added value. This may still be a step too far for hiring teams inching towards the use of people analytics, or who have yet to harness the insight available in basic recruitment metrics. Deloitte’s Global Talent Trends report for 2017 shows that 85% of companies have usable data but only 9% have a ‘good understanding of which talent dimensions drive performance’. Dark data may be the key to understanding those dimensions.

About the Author:

Kate Smedley

Kate Smedley is a freelance copywriter specialising in HR, HR Tech and recruitment, with 18 years of previous experience as a recruiter. Kate also works with employers to identify problems in hiring processes, offering full support and advice throughout the recruitment cycle.


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HR's Aversion To AI Will Affect Its Ability To Hire

HR’s Aversion To AI Will Affect Its Ability To Hire

Artificial Intelligence

Successful hiring should be based on evidence based decisions supported by technology and automation but HR remains slow to respond. PwC’s 20th Global CEO Survey found that nearly half (47%) of UK CEOs are failing to address the impact AI and automation will have on their businesses (compared to 31% globally and just 19% in Germany). As 83% of UK CEOs rank access to skills as their number one barrier to business success in the next 12 months, this needs to change.

Why the reluctance to engage?

HR has often demonstrated a wariness of data and more recently automation and AI, exacerbated by recent headlines including:

  • Fukoku Mutual Life Insurance in Japan announced its intention to automate the jobs of over 30 employees, replacing them with IBM’s Watson Explorer. According to the Nomura Research Institute, half of all jobs in Japan could be performed by robots by 2035.
  • A similar scenario was projected in the UK, with the prospect of 15 million jobs being eradicated by AI, shortly after an announcement that outsourcing specialist Capita was replacing 2,000 of its employees with automation.
  • The world’s largest hedge fund, Bridgewater Associates intends to automate three-quarters of its hiring decisions over the next five years. The company is building a robotic recruitment platform to remove ‘emotional volatility’ from business decision.

How AI and automation empower HR

AI and automation offer a number of benefits for HR:

Talent pipeline : In its simplest form automation identifies issues in your talent pipeline, such as, qualified candidates abandoning a prolonged application process. Algorithms are also used to reveal factors which improve employee engagement and identify leadership potential. This is relevant in a week when a Robert Half survey found that that half of all candidates for management level roles don’t possess leadership skills.

More effective candidate selection : HR has historically relied on standard but limited candidate selection criteria, such as interview performance or an emphasis on technical skills or qualifications but that isn’t sufficient to predict a quality hire. Broader, evidence based HR is needed to support effective candidate selection, which algorithms in your recruitment software offer.

Potential flight risks : Combined with predictive analytics, algorithms can also predict potential flight risks in your organisation. With an expected talent exodus in 2017 understanding why your high achievers leave is critical. Typical ‘prompts’ include birthdays (especially milestones) and work anniversaries but your own recruitment metrics will provide more insight.

Reduction in bias : Automation and AI help to eradicate unconscious bias. This is exemplified by the tendency to hire so-called ‘brogrammers’ across the US’s Silicon Valley, fuelling the image of a male dominated tech culture. Closer scrutiny revealed that the majority attended elite schools and secured their jobs through friends or the tech fraternity. AI start-up Tara.ai aims to change that bias. Tara removes information relating to age, gender, previous employment, education and race to assess candidates based on the quality of their work – analysing and ranking programmers’ code – rather than their personal connections or background. Selecting specific criteria within your applicant tracking software helps to achieve the same results.

Technology needs the human touch

Should HR be wary? Algorithms in the hiring process have been proven to make better hiring decisions than humans but the role of HR, while shifting, is integral to the future of AI.

The following strategies can help to make the vital transition to evaluating the benefits of AI and automation in hiring:

  • Technology is only as effective as the information gathered. Inputting bad data will produce poor quality results. The quality of your data is vital.
  • When posting open jobs, understand the precise skills you need from your new hire. A candidate persona improves recruitment success for either high volume or stand-alone critical positions.
  • Algorithm or AI averse hiring teams can begin with automated recruitment software that streamlines the hiring process and analyses the common patterns revealed in your recruitment metrics. Start by focusing on just one specific area. With qualified candidates in short supply, time to hire is one of the most important metrics your business can measure and allows HR to evaluate the effectiveness of automated recruitment systems.
  • Create a structured interview process supported by online tests during screening to assess cognitive ability, conscientious and leadership.
  • Final decisions on candidate selection should be collaborative and supported by relevant data gathered during the hiring process. The CIPD found that, in organisations that use HR analytics, a quarter of senior leaders are not being given access to HR data to make effective business decisions. Without data, your ability to attract and hire high achievers is restricted.

HR technology should be simple to use, easy to engage with and produce data which informs and drives talent acquisition strategies.

Introducing a ‘kill switch’?

While AI and automation are now unavoidable, justifiable concerns exist over its growing impact on the workplace. In response to these concerns, the European Commission’s Legal Affairs Committee is seeking the creation of a European agency to provide technical, ethnical and regulatory advice on robotics and AI within the EU. Its proposal recommends:

  • A voluntary code of conduct related to AI.
  • A ‘kill switch’ in all AI systems to ensure they can be automatically deactivated in the event of a malfunction.
  • Consideration of a minimum income to compensate people who have been replaced by robots in the workplace.
  • A new status of ‘electronic persons’ for autonomous robots.
  • Reassurance that the use of robots does not engender ‘fear of physical or psychological harm’, while maintaining privacy, human dignity and safety.

HR is a long way from dealing with those issues on a daily basis but employers must begin now to address the impact of AI and automation in the working environment to remain competitive and meet future business goals.


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4 Ways To Transform Talent Management Success With AI

Artificial Intelligence in HR

The technological revolution continues to gather pace. Investment in AI is expected to grow by over 300% in 2017 compared to 2016, according to research consultancy Forrester in its report : Predictions 2017 : Artificial Intelligence Will Drive The Insights Revolution. Used effectively, automation and AI empower employers to create effective talent management strategies. Here are just four for 2017:

Future Workforce

Tapping into the gig economy : Workforce models are evolving to encompass gig economy, contractors and part-time workers within traditional recruitment workforce planning systems. In the UK alone, one million people are now agency workers but there is a clear distinction between agency and the ‘open talent’ workers of the gig economy. Evaluate the source of your most successful employees with recruitment analytics and expand your talent pool to incorporate gig economy workers on vital roles. 70% of gig economy professionals have over 10 years of experience in their market and will prove to be a valuable resource as skills in sectors such as tech and engineering become more scarce.

Recognising the disconnect : The growing popularity of a freelance career is expected to lead to a fall in employee loyalty but it goes beyond contingent workers. Hays UK Salary and Recruiting Trends 2017 survey found that, while nearly a quarter of employees consider work/life balance important, only 13% of employees feel the same way. Recognising the disconnect that exists between HR and its employees is essential to improve engagement. The Institute of Leadership and Management refers to this disconnect as a ‘leadership lag’. Measuring employee retention levels through data analysis will provide insight into the success of your talent management strategy and enable HR to deliver change.

Engaging candidates : Chatbots are predicted to play an increasingly interactive role in hiring. Jobseeking company Fastjob trialled chatbot Mya earlier this year. Mya is designed to take over 75% of the recruitment process, utilising a combination of AI and natural language processing (NLP). Early trials indicate that candidates who engaged with Mya were over three times more likely to be contacted by a hiring manager. Chatbots are also considered more suited for mobile than apps. In a further development, the Financial Times also reported last month on robot hiring manager, Matlda. Still in the research stage, Matlda is designed to shortlist and interview job applicants. Successful hiring means engaging with technology. Companies choosing to stay with the familiarity of manual recruitment systems will fail to attract high achievers. HR technology is the first step ensure your company is poised to compete in a candidate driven market.

talent

Monitoring wellbeing : A focus on workplace wellbeing will be central to successful talent management in 2017. For instance, the global workplace is facing a sleep deprivation crisis. In the UK alone, sleep deprivation costs an estimated £40 billion per year, or 200,000 working days, according to RAND Europe. The US loses 2.28% of its GDP – up to $411 billion and 1.5 million days – due to sleep deprived employees. As wearables begin to incorporate AI, HR can tap into technology to monitor sleep patterns and implement policies to improve employee wellbeing. 56% of people would be happy to allow employers to collect data from wearable technology provided there was a related benefit, although it should be noted that 41% don’t trust their employer not to use the data against them. Implementing a clear policy for ensuring the ethical and confidential use of the data gathered is essential.

Writing in Harvard Business Review Andrew Ng observes that ‘if a typical person can do a mental task with less than one second of thought, we can probably automate it using AI either now or in the near future.’ Engaging with automation and AI, empowers HR to rapidly respond to and engage with ongoing changes in the workforce and labour market. HR technology is your first step towards achieving that goal in 2017.

Advorto’s recruitment software provides workflow and structure across the entire hiring process, offering a dynamic database of candidates and analytics. Used by some of the world’s leading organisations, it provides a straightforward first step into HR analytics and big data.


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Breaching The Big Data Barrier : Moving HR Towards Analytics

big-data

Investment in big data has risen in 2016. That’s according to tech consultants Gartner which reveals that 48% of companies invested in big data this year, an increase of 3% compared to 2015. Planned investment in the next two years is predicted to fall, however. The issue, according to Gartner, is not so much the data but how it is used. 85% of companies who invest in big data remain in the pilot stage as projects fail to progress beyond the initial commitment.

That is certainly the case for the UK which is ranked 14th in the world for digital adoption. As candidate availability falls and the digital skills shortage spirals towards a critical point, big data is HR’s path to navigating through the complex issues affecting the workforce. Breaching HR’s innate big data barrier to move towards analytics requires a clear strategy. Here’s how to achieve that:

Evaluate your current position : Understanding the maturity of your current recruitment process will provide a base from which to evaluate progress. Deloitte’s Global Human Capital Trends Survey 2016 found that one third (32%) of businesses felt ‘ready or somewhat ready’ for analytics while 8% believed they were ‘fully ready’ to develop a predictive model. Know your starting point.

Aim for quick wins : PwC’s 2016 Data and Analytics Survey reports that UK executives want more data driven decisions but are held back by their organisations and culture. Demonstrating the benefits with some quick wins will help to overcome internal resistance to big data. Aim to provide insight and solutions into ‘roadblocks’ within your hiring process. For example, a lengthy application process deters candidates from completing application forms, while recruitment analytics identifies the source of your best applicants. Begin with HR technology covering key hiring metric which extracts information from live data within your Excel spreadsheets. Getting the right data is the key, whether ‘big’ or ‘small’.

Collecting data : Most companies have a wealth of data available. Collecting, analysing and understanding that data is the biggest challenge. For example, most hiring teams have access to a wealth of information available from sources such as social media, in-house surveys and LinkedIn. That data provides a starting point and may include:

  • Performance management reviews.
  • Personal data, including medical history and employee attendance levels.
  • The hiring sources of your most successful people..
  • Employee participation in surveys and candidate referral schemes.

Utilising analytics : Big data helps to shape your understanding of the online habits of your talent pool, through tracking their digital footprints. It assists evaluation and targeting of job posts and facilitates engagement with people who possess the skills critical to your business. That information helps to create focused candidate personas in order to target future recruitment at relevant talent pools. Analytics evaluates the demographic profile of potential hires, coupled with their educational background, career history and typical salary. Advanced analytics can predict talented employees who may be a ‘flight risk’. When high risk people are identified, HR can adopt a more effective and aggressive retention strategy, focusing on areas such as career development, in-house training and flexible working.

Minimising bias : Data helps to reduce ‘confirmation bias’, broadly defined as a pre-existing belief we may hold which we look for evidence to support. In hiring, this may present itself in repeatedly recruiting applicants from the same social or education backgrounds. The Social Mobility Commission’s newly released State Of The Nation Report 2016 reveals the extent of the problem in the UK, noting that only 4% of doctors, 6% of barristers and 11% of journalists are from working-class backgrounds. Confirmation bias leads HR to eliminate talent from interview selection. Hiring algorithms in big data help to prevent that. As a prime example, Google’s re:Work platform operates on the principle of ‘unbiasing’, which it states begins with ‘education, accountability, measurement and more’.

Don’t over-invest : Big data must work for your business. Scalable HR technology enables your business to expand as employers analyse and interpret the data available. Recruitment software without integrated analytics that provide live and instant data will hinder, not help your hiring process. It should also be mobile friendly and equipped with social collaboration tools.

Ensure ethical use of data : Confidentiality and privacy must be a priority for employers collecting data on candidates which includes personal information. The UK government has accepted a recommendation to create a council of data science ethics to address concerns over the misuse of big data. Establish ground rules for the use of talent analytics within your business to ensure compliance. Choose technology that complies with the Data Protection Act and offers a full audit trail.

Treat big data as your ally

Big data is here to stay. The Economist Intelligence Unit reports that, while cyber-security and web/mobile development are the highest ranked competencies today, big data will replace them by 2018.

Big data is HR’s ally. Utilised effectively it augments recruitment and selection decisions by providing objective data that highlights disruptive elements in the hiring process. No data is perfect but it provides an indication of activity and progress in your talent management strategy. Create a story and positive message around your technology to empower HR. It isn’t about statistics. It’s about enabling your business to create stronger talent pools, and a more robust hiring process.

HR must develop familiarity with and insight into data to communicate its benefits confidently and ensure that it aligns with performance objectives. Adopting a predictive talent model is your goal but breaching that big data barrier is the first step.

Advorto‘s recruitment software provides workflow and structure across the entire hiring process, offering a dynamic database of candidates and analytics. Used by some of the world’s leading organisations, it provides a straightforward first step into HR analytics and big data.


If you want to share this article the reference to Kate Smedley and The HR Tech Weekly® is obligatory.

Changing HR : AI At Work

12186039 - human head.figure the concept of artificial intelligenceData driven recruitment has a significant, positive impact on talent management strategies and business performance. As technology becomes more sophisticated, AI is playing an increasingly essential role in decisions made around hiring and is used by brands such as Facebook as an integral part of the screening and assessment of candidates.

This article examines its ongoing effect on the jobs market and the ways in which HR can harness its advantages to better understand, improve and predict hiring needs and potential problems.

Changing employment sectors

AI is broadly defined as ‘machines which perform tasks which humans are capable of performing’. It has been traditionally been regarded as a threat to jobs, with the most drastic predictions suggesting that unemployment rates will reach 50% within 30 years, but perceptions and predictions are changing.

Rather than AI leading to a jobless future, the 2016 report from Stanford University’s One Hundred Year Study on Artificial Intelligence suggests that AI will be regarded as a ‘radically different mechanism for wealth creation’ replacing ‘tasks rather than jobs’ and leading to the creation of new types of jobs.

To give this some context, a reported 60% of existing retail jobs have a ‘high chance’ of automation by 2036 but a new sector of e-commerce has emerged in response to this change. As predicted by Deloitte, high risk jobs are being replaced by more creative low risk jobs with each new job paying a salary £10,000 higher than the one it replaced, in the process adding £140 billion to the UK economy. This shift is also apparent in the rising demand for specialist tech skills in areas like data analysis across all sectors.

Stanford University’s 2016 report also concludes that the impact of AI isn’t limited to medium skilled jobs but will invade ‘almost all employment sectors’ affecting the higher end of the job spectrum, encroaching on professional services and impacting even cognitive roles.

The need for the human touch

The proliferation of AI is not without its problems, however. AI-averse HR leaders have enjoyed some justification for their reluctance to engage with technology in recent months. To add to the negative publicity generated by Microsoft’s Twitter bot, Tay, Facebook has faced criticism after replacing its ‘trending’ team with algorithms, which led to the publication of false and inappropriate links. More relevant to HR was LinkedIn being forced to deny claims of gender bias in its search algorithm.

AI is most effective when combined with the human touch. It is based on mathematics; when harnessed within HR technology, it improves the hiring process, from candidate screening to onboarding, enabling HR to create more effective talent management strategies. AI is a collaborative robot or ‘co-bot’ as it is referred to, freeing people to carry out more productive tasks.

Technology and the competitive advantage

Technology is vital to the future of the workforce, giving employers a competitive edge. A study from Oxford Economics, entitled Leaders 2020, found that the most successful businesses are one and a half times more likely to use technology. It also reiterates the following:

  • The businesses it describes as ‘digital winners’ have strong talent acquisition strategies and provide updated technology to their employees.
  • These organisations also tend to have happier and more engaged employees.

Of concern was the fact that less than half of respondents stated that their company leadership was ‘highly proficient’ in using technology, a growing problem in the UK’s economy.

Incorporating AI into the recruitment process

AI should be regarded as critical to all businesses. It guides HR to make better decisions, ‘replacing tasks rather than jobs’ and driving improvements across the following areas:-

  • Improving talent acquisition : Your business will be better informed and able to predict future hiring needs, source people more quickly and identify skills gaps within your existing workforce. HR technology is the first step towards identifying those gaps.
  • AI, in the form of HR analytics, helps to improve diversity and reduce bias in recruitment. Diversity means hiring the best candidate for a position who will also fit well with your existing team. The Oxford Economics report found that a diverse workforce results in higher revenue and profitability.
  • HR analytics provides insight into the historical success of your hiring process, enabling HR to eliminate poor hiring decisions, cutting out the need for ‘gut feel’ and guess work. It also predicts the candidates most likely to succeed.
  • Improving retention : AI can quickly identify factors affecting high staff turnover. For example, your current pay scale may match the market but if it veers towards the lower end, your business risks losing talent to your competitors. HR analytics enables identification of those patterns within your organisation.
  • HR analytics predicts the skills needed for your future workforce,  equipping HR with vital data needed for effective planning. In a knowledge based economy, the World Economic Forum predicts that a combination of mathematical and interpersonal skills will be among those in highest demand. Traditional educational models coupled with a lack of vital skills in the UK are leading to a mismatch of talent, however. To be truly effective, a ‘joined-up’ HCM process begins with a recruitment management system that integrates ongoing employee skills assessment and training.
  • Drives hiring based on talent : Facebook recently revealed one of the central components to its hiring strategy, namely Marcus Buckingham’s and Curt Coffman’s book “First, Break All the Rules.”, first published in 1999. It recommends that the primary focus in candidate selection is on talent, which they describe as a ‘recurring pattern of thought, feeling or behaviour that can be productively applied’. Technology provides a range of techniques from sophisticated screening through applicant tracking software and online assessments to virtual reality such as video interviews enabling HR to identify, focus on and hire talent.

Advorto’s recruitment software provides workflow and structure across the entire hiring process, offering a dynamic database of candidates and analytics. Used by some of the world’s leading organisations, it provides a straightforward first step into AI, HR analytics and big data.

Start your 30 day free trial today.

You might also like to read:

HR Holds The Key To Business Success With People Analytics

Data Driven Recruitment : What’s Holding HR Back?

For more insight into the trends shaping the retail sector, download our in-depth Retail Sector Focus.


Source: Changing HR : AI At Work