AI-Powered Interview Chatbot

AI in Recruiting

The world around us is in a constant state of flux. We may not like it but no one can deny that the world is changing. Some of these have been for the good while others not so much. The recruitment industry has not been immune to these changes.

The way that we recruit has undergone several transformations. Of these, the most important and most radical one is its latest iteration, the AI revolution in recruitment.

The impact of AI in recruitment has been well documented as far as the recruiting side is concerned. What has been less explored is its effect on the candidate.

With more and more companies adopting AI for their recruitment process, candidates too should keep up with the changing landscape. A candidate should be prepared to be interviewed by a machine just as much as they are to be, by a human.

Practice for an AI recruiter

Practice may not make one perfect but it sure as hell does help. There is a reason why any respectable university or college conducts placement training with mock interviews, for its students.

Click here to go to the practise bot

If you want to practice for an interview conducted by a human it’s rather easy. There are thousands of avenues to practice for a classical interview.

So how do you practice for an AI interview? Fear not! that’s why we are here.

We at Impress have developed a practice chatbot which tries to imitate the real thing as far as possible. Our actual bots usually have external assessments, which is not present here because it depends on third parties.

How to take the test

Do keep in mind that the questions are significantly easier than in a real test. If you answer the questions sincerely and complete the application we will even send you the result of the interview.

Whenever you are ready just click on the robot below to start your practice interview.

When AI and Data Analytics Meet Healthcare

The Telegraph covered a robotic revolution in the healthcare sector and predicted an increase in robotic systems in hospitals in the coming decade. Insights from 2016 indicate that about 86% of healthcare provider organizations and technology vendors to healthcare are using artificial intelligence technology. Institutions across the globe are adapting to automation, machine learning, and artificial intelligence (AI) including doctors, hospitals, insurance companies, and industries with ties to healthcare.  Here are a few of the many ways AI and data analytics are paving the road to better healthcare

1. Mining Medical Records and Devising Treatment Plans

In a day, a radiologist attends to almost 200 patients and 3000 medical images. Today, every person who visits a medical practitioner has their medical record created. The number of records will only grow in the coming years. Analysing this data and determining a treatment plan consumes valuable time. AI can help reduce the workload and expedite the medical process with the help of something called as a Patient Data Mining.

MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) created ‘ICU Intervene’, a machine-learning approach that collects a significant amount of ICU data ranging from medical to demographic details. Through this data, the AI can determine the types of treatment the patients need and quicken the diagnosis to save critical time.

A community hospital in Florida, the Flagler Hospital has created a CarePath for every patient admitted from Pneumonia or Sepsis. This CarePath has traced a Data Group called the Goldilocks groups, which had the lowest length of stay, lowest readmission rate, and lowest cost paid. The process followed for these patients led to the best possible outcomes. This helped the hospital trace what should ideally happen in the emergency room in a sequence.

This pathway is expected to cut length of stay by two days and save $1,356 per Pneumonia patient. They also found the readmission rate reduced from 2.9% to 0.4% of total patients.

“Data gathered and presented by AI algorithms will enable healthcare providers and doctors to see patients’ health risks and take more precise, early action to prevent, lessen the impact of or forestall disease progression. These interventions will curb healthcare costs and lead to improved patient health outcomes,” said Derek Gordon, COO of Lumiat, to Cygnismedia.

2. Assisting in Repetitive Jobs and Future Prediction

Routine jobs such as X-rays, CT scans, and data entry can be offloaded to an AI assistant.

In cardiology and radiology, not only does analysis and compilation of data consume crucial time but is also prone to trial and error. AI can prove to be more accurate and helpful in such scenarios. It can read CT scans and medical reports to provide a diagnosis of similar images stored in the database.

In fact, a Chicago start-up, Careskore uses a cloud-based predictive analytics platform. Using Zeus algorithm in real time, Careskore predicts the likeliness of an individual’s hospitalisation after studying a range of data which includes a combination of behavioural, demographic and clinical data.

3. Blending Physical and Virtual Consultations

Chat bots used in the healthcare sector interact with the patients through telephone, text, or website to schedule appointments and follow-ups, billing, processing 24×7 urgent requests for customer care, and so on. They help in reducing the overall administrative cost of the hospital.

Medical Virtual Assistants (MVA) collect and compile a patient’s medical and demographic details. M-health apps help people track their health and notify patients about upcoming appointments. They are also programmed to answer the basic health-related or medical queries of a patient.

A great example of MVA is Sensly, it is an avatar-based clinical app. It helps clinicians, caretakers, and patients better monitor and manage their health. It has deployed the first fleet of AI powered nurse-avatars to clinics in San Francisco. It focusses on creating an effective communication channel to avoid repeated hospital admissions.

According to The Medical Futurist, UK desires the following solutions from a Health app;

4. Medication Management

AI-enabled systems can track patients’ data and suggest treatments based on analysis. An Israeli start-up developed AI algorithms closely accurate or even more precise than humans when it comes to the early detection of conditions such as coronary aneurysms, brain bleeds, malignant tissue in breast mammography, and osteoporosis. This way AI can become an active part of clinical-decision making. In a recent article by Wired, it’s stated that AI is 99% accurate and 30 times faster in studying and translating mammograms, allowing much earlier detection of breast cancer than human doctors can. Such assistance can significantly augment the medical procedure.

In order to monitor the use of medication by a patient, National Institutes of Health have created an app called AiCure. This app uses the phone camera to track the dosage. It has been a significant contributor when it comes to patient who tend to go against the Doctor’s advise or suffer from serious medical conditions.

[According to Enlitic, a medical startup, “Until recently, diagnostic computer programs were written using a series of predefined assumptions about disease-specific features. A specialized program had to be designed for each part of the body and only a limited set of diseases could be identified, preventing their flexibility and scalability.”

Also, AI is becoming crucial to improve data documentation and indexing in electronic health record (EHR) systems. Even though the EHR platforms continue to proliferate, navigating and accessing data from these platforms have remained inconvenient for most of the healthcare providers. In fact, most of them find these systems inflexible and costly to configure. AI facilitates accurate data extraction and clinical documentation. Subsequently, it helps delivery networks develop predictive algorithms for health prediction and diagnosis. For instance, Google and Enlitic are working on AI-based image interpretation algorithms. Also, AI-derived EHR platforms render support in making clinical decisions and devising treatment strategies

5.Blockchain Can Enable More Efficient HER

Seamless interoperability of electronic health records (EHR) is crucial for accurate medical data management. However, that’s exactly the problem healthcare providers are frequently facing. According to John Meigs, Jr., MD, Board Chair, American Academy of Family Physicians, “For the most part, the different EHR software programs available don’t talk to each other and in fact make it extremely difficult to exchange data across systems.”
Blockchain can make EHR more convenient and easy to use. Blockchain helps EHR to show date from multiple databases added in the ledger instead of a single data base. Here, blockchain acts as a decentralized control denying any exclusive ownership to data, but at the same time making it available for everyone. Eliminating an organization between the patient and his/her records is the biggest advantage of using blockchain enabling a more secured process of data exchange

6.Finding the right Talent in Healthcare

As the healthcare industry grows, there is always a need for qualified healthcare professionals. Often, hiring managers receive hundreds of resumes per open role. When shortlisting candidates for interviews, they use various data points such as filtering out candidates with too many or too few years of experience. Beyond this level of filtering, many companies are using AI chatbot software for recruitment. For example, Accenture uses Min, an AI virtual recruiter to hire data scientists in Singapore. This helps recruiters save time, improve efficiency, and make fair hiring decisions. For candidates, the chatbot engages, interviews, and shortlists them 24/7.

7. Helping People Make Better Health Choices

Based on the demographic, behavioural, and medical data of people, AI-enabled systems can predict health risks in advance and warn people accordingly. Six months after El Camino Hospital in Silicon Valley applied artificial intelligence, the rate of patients with fatal diseases fell by a 39 percent.

The most popular example of an instrument helping people lead healthier lives is the FitBit or other healthcare trackers. They are easily available, trace trends, and set health targets.

These apps and trackers can efficiently track a lot of data and guide humans to lead a healthy lifestyle. On the basis of the demographic, behavioural and medical data of people, AI-enabled systems can predict health risks in advance and can warn people accordingly.

As per OECD estimates and figures from The United States Institute of Medicine, the top 15 countries by healthcare expenditure waste an average of between $1,100 and $1,700 per person annually. Health App Solutions offered by AI helps healthcare systems avoid needless hospitalisations.

Not only does Data Science help Doctors by advising treatment solutions, but also enables people to lead a better and healthier lifestyle. 

References

http://news.mit.edu/2017/using-machine-learning-improve-patient-care-0821

https://www.cygnismedia.com/blog/how-artificial-intelligence-transforming-modern-healthcare/

https://sanvada.com/2017/12/15/how-companies-are-using-ai-in-the-field-of-patient-data-mining/

https://www.usnews.com/news/healthcare-of-tomorrow/articles/2017-10-31/hospitals-utilize-artificial-intelligence-to-treat-patients

https://searchhealthit.techtarget.com/tip/Four-uses-for-artificial-intelligence-in-healthcareps://searchhealthit.techtarget.com/tip/Four-uses-for-artificial-intelligence-in-healthcare

http://medicalfuturist.com/chatbots-health-assistants/

http://medicalfuturist.com/artificial-intelligence-will-redesign-healthcare/

https://www.healthcareitnews.com/news/flagler-hospital-uses-ai-create-clinical-pathways-enhance-care-and-slash-costs

https://www.weforum.org/agenda/2018/05/four-ways-ai-is-bringing-down-the-cost-of-healthcare/https://hbr.org/2018/12/using-ai-to-improve-electronic-health-records?autocomplete=truehttps://hbr.org/2017/03/the-potential-for-blockchain-to-transform-electronic-health-records?autocomplete=true


Why you should consider AI chatbots in your recruitment strategy

Guess how much a bad hire can cost your company?

Anywhere between $25,000 – $50,000. That’s quite a heavy hit for any company.

Although these figures come across as daunting, Artificial Intelligence (AI) is increasingly being woven into recruitment workflows to prevent hiring managers from making less-favourable decisions to begin with. As resumes pile up, it’s challenging to determine which candidates are the best fit in terms of experience, knowledge, and cultural fit. AI not only eases crucial parts of the recruitment processes, but also provides several benefits for both recruiters and candidates.

Here are the top benefits of using AI in recruiting:

1. Removing bias from your recruitment workflow

The first aspect of any resume that catches a recruiter’s eye is the name printed across the top. That name indicates attributes about a candidate, like gender and ethnicity. Whether consciously or not, a candidate’s name can affect their likelihood of getting the first interview call. Bias in the hiring process is still one of the most critical hindrances to quality recruiting. This is evident in how minority job applicants are “whitening” their resumes by deleting references to their race in hopes of boosting their shot at landing the first interview. What’s concerning is that this strategy has been paying off. An article published by Forbes claims that hiring managers are more than 2X as likely to call a minority candidate for an interview after they submit a “whitened” name on their resume compared to candidates who reveal their race.

A common hiring practice across the world when meeting candidates face-to-face is judging candidates based on “gut” feel or unconscious bias stemming from a hiring manager’s upbringing or previous experiences. One way to eliminate hiring bias and improve workplace diversity is to implement an AI software for recruitment. Because AI algorithms stem from data intelligence, they can identify and eliminate biases, both conscious and unconscious. This increases the likelihood that candidates are chosen based on their talent, knowledge, and capabilities as opposed to their gender, race, or name.

2. Filtering out top quality candidates

The quality of your applications depends on the initial candidates you’re attracting. The type of candidates (as well as the volume) of candidates that apply to open positions at your organization correlate directly with the reputation of your organization and employer branding. In the early stages of the applicant filtering process, AI can help assess candidates based on criteria beyond what’s listed on a resume, like their intent and motivation.

Pro tip: One tool that can help you to screen and qualify candidates is impress.ai, an AI chatbot software for recruiters. The platform engages and assesses candidates based on pre-screening questions, scenario competency based questions, and knowledge based questions. According to Nisa Rahman from The Creative Square Company, “I like how the platform has changed my perception. When I look at what the candidate says on the screen, it shows a different side to them that I wouldn’t have seen on their CV. A lot of candidates are also able to share better insights when typing out responses. Plus, if the interview is recorded, I can refer back to it later for reference before having the the face to face interview.” Read more about her experience using AI chatbots for recruitment here.   

3. Creating a more positive and engaging recruitment experience for candidates

Recruitment is the gateway into any company; it’s where first impressions are made. Since engaging candidates is an important part of the recruitment process, many AI recruitment tools are created with candidates in mind, making the hiring process a positive experience for both, recruiters as well as candidates.

When candidates can easily get answers to their questions and access information instantly, they’ll feel more compelled to stay connected with your organization. If they’re having a positive experience while applying to an open role, they’ll be even more excited to come onboard.

On the reverse side, if a candidate applies to a company and receives an automated rejection email without any clear reason, or worse – no reply at all, they are likely to walk away from that experience with a negative view of the brand. Candidates are very likely to share these negative experiences online, with their friends, and their family. According to CareerArc’s research, 72% of candidates who had a bad experience told others about it.  

One possible reason why candidates go through experiences like these are because in-house recruiters are inundated with busy tasks, which can lead to applicants falling through the cracks or slow response times. You may be surprised to know that 65% of resumes are ignored at the top of the hiring funnel, and almost 2/3 of applications are missed by recruiters. And this is largely due to the burden of manual screening. Incorporating AI-powered chatbots provides a a better communication channel because recruiters have more time to spend on work that requires actual human interaction. Automation ensures that qualified candidates will stop slipping through the cracks.

It’s frustrating for candidates to send follow-up emails and wait endlessly. By eliminating hurdles in the hiring process, more candidates are likely to complete an interview application, creating a smoother recruitment experience for both parties. For example, Forbes published an article about how DBS Bank uses JIM, an AI virtual recruiter to respond to 96% of all candidate queries and improve completion rate of job applications from 85% to 97%.

Pro tip: HR software can guide candidates through a step-by-step interview process so their interest is acklowelged and appreciated. These systems can be programmed to let selected candidates know of next steps in the process immediately. And if candidates aren’t suitable for the role, they can be notified of better fit opportunities within the organization.

4. Saving time by automating manual tasks

Recruiters spend up to 1/3 of their time dealing with tasks like scheduling and screening. When these tasks aren’t taken care of, workflows can are disrupted and candidates are left wondering about next steps in the hiring process. Most mundane tasks that recruiters would rather not deal with can be automated using AI. Many of these tasks involve repetition and are time-consuming. One way to save time and automate these low-value tasks is by introducing an AI system into the recruitment process. This frees us time for your recruiters to focus on the high value activities, like building relationships with quality candidates.

Building relationships is key. When you’re able to establish true connections with applicants, they get excited about your company’s values and goals. Your new hires become intrinsically invested in the organization, encouraging them to stay around longer, while also allowing your team to get more done.

Pro tip: From resume screeners to scheduling software, the HR technology industry is overflowing with automation software created for recruiters to overcome these common everyday challenges. AI chatbots offer a great way to improve efficiency and save time. Read our featured case study about a Singapore bank that saves up to 40 man-hours per month using AI recruitment bots.

5. Hiring that is cost effective

Advertising agency fees, recruiter salary and benefits, employee referral bonus, employee relocation costs, sign-on bonuses, and more. These all factor into hiring costs and depending on the industry your team works in, hiring costs can range anywhere between $1,000 – $5,500.

Although AI systems normally come with costs to the department, it should be seen as a long term game with a positive impact on long-term ROI.

Not only will AI reduce your need to hire additional recruiters to complete manual tasks which could have been otherwise automated, the system can help hiring managers make more informed decisions so the right candidate is given an offer letter the first time around. You’ll also see reduced turnover rate and save money on training, signing bonuses, and other expenses associated with onboarding new employees.

6. Optimizing recruitment processes

If recruitment processes are lengthy and complicated, top talent can easily turn to your competitors. When determining how optimized your team’s hiring process are, start by looking at recruitment metrics. This is an area where AI excels – compiling large amounts of data and turning it into easy-to-understand charts. Recruiters who haven’t been trained in analytics are often able to extract just enough insights to see where their process is lacking and how to use data for improvement.

Common recruitment metrics to track include:

Time to hire

Time to hire is the number of days between contacting a candidate until the time that candidate accepts the job offer. In other words, it measures the time it takes for the candidate to move through the hiring process once they’ve applied. Time to hire provides an indication of how the recruitment team is performing. This metric is sometimes referred to as ‘Time to Accept’.

Cost per hire

The cost per hire is the total cost invested in hiring divided by the number of hires.

= Total recruitment cost/Total number of hires

= Total internal cost + Total external cost/Total number of hires

Employee retention rate

Employee retention rate is a helpful statistic for an employer to calculate, both as a benchmark as well as periodically.

Here is the formula: Divide the number of employees who left during a specified time period by the total number of employees at the end of a period to get the percentage.

Sample InputsSample Calculation
Period of Time: First QuarterTotal Employees at Beginning of Q1:25Total Employees Terminated in Q1: 525 – 5 = 20 20 / 25 = .80.80 x 100 = 80%

Standard employee retention rates fall anywhere from 70% – 85% but vary based on industry and calculation method.

Pro-tip: If you’d like to see what your recruitment metrics dashboard could look like, email contact@impress.ai to start optimizing your recruitment processes.

PwC named AI one of the top eight technologies in business, and IDC predicts AI will be a $47 billion market by 2020. AI is a disruptor, and it is making the world of talent acquisition smarter. If you’re not adding AI into your recruiting process, or at least reading up on the possibilities, you’re definitely missing out.

Is your team ready to experience how AI can improve recruitment processes? Email contact@impress.ai today. We’ll show you a easier way to overcome your hiring challenges and transform how your team finds top talent in 2019.

Singapore Salary Guide for Data Scientists in 2019

The top five emerging jobs in Singapore today are data scientist, cyber security specialist, user experience designer, head of digital, and content specialist. As the demand for digital talent continues to rise, jobs in data science have grown by 17X between 2013 to 2017. And along with that spike, salaries of professionals working in this field have also steadily climbed.

Our team at impress.ai has created a salary guide for data scientists in Singapore, which outlines everything you need to know from the average salary to the factors involved in getting that next big pay bump:

What is the average data scientist salary in Singapore?

According to PayScale, The average pay for a data scientist in Singapore is S$72,109 per year. The typical salary ranges from S$45,325 – S$112,491, with an additional bonus ranging from S$1,007 – S$20,204. Most corporates also offer employees health benefits; 87% cover medical, 34% cover dental, and 14% cover vision.

Looking for a data scientist job in Singapore?
Accenture is currently hiring over 50 qualified data scientists in Singapore.
Here’s your chance to work at the cutting edge of innovation:
Find out what Accenture is looking for in candidates on their careers page or skip the queue and talk to Min, their AI virtual recruiter who is currently interviewing and shortlisting data science candidates!


What variables affect my salary as a data scientist?

The most common factors that determine how much you get paid include years of experience, skills, and sector. For example, the average annual salary of a junior data scientist is S$59,480, whereas a mid-level data scientist earns S$104,626, and a senior data scientist could earn S$136,783.

What tools should data scientists know to get paid more?

The tools that data scientists know how to use also play a crucial role in compensation. Using big data tools like Scala and Spark could add $15,000 to your salary. And negotiation often leads to a 7% bump in salaries–even though 18% of all people never negotiate their salaries.

Top tools data scientists in Singapore should know to get a higher salary:

According to O’Reilly’s Data Science Survey:

  • Learn Spark and Scala: could add up to S$15,000 to your salary
  • Learn D3, a Javascript visualization library: correlation of a S$8,000 positive boost
  • Become comfortable with cloud computing, especially Amazon Web Services: boost of about S$6,000 in annual salary
  • Familiarise yourself with open source tools and stay away from proprietary tools
  • Become versatile and learn how to use many tools (aim for 15+): could add up to S$30,000 to your annual salary

The main takeaway from the O’Reilly Study is that there are nine main clusters of tools that data scientists use everyday, ranging from the Hadoop ecosystem to the open source environment, to Python, and the closed Microsoft SQL cluster. Most data scientists learn tools within a cluster, as the tools complement one another within. Professionals who tend towards closed Oracle and Microsoft tools will earn less, while those who flock to open source clusters are likely to earn more.

How does industry impact my salary as a data scientist? 

Apart from companies in the search and social networking space, consulting companies like Accenture pay data scientists well.

Looking for a data scientist job in Singapore?
Accenture is currently hiring over 50 qualified data scientists in Singapore.
Here’s your chance to work at the cutting edge of innovation:
Find out what Accenture is looking for in candidates on their careers page or skip the queue and talk to Min, their AI virtual recruiter who is currently interviewing and shortlisting data science candidates!

YourStory Start-up Dialogue

Startups are known for their speed, innovation, and taking risks, however they often find it challenging to scale. Enterprises, on the other hand, rely on their proven brand presence to scale but find it challenging to take risks. Working together, they can help each other reach positive outcomes. According to KPMG’s New Horizons study, 94% of startups would like to repeat a collaboration process with larger organizations. And based on Imaginatik’s The State of Startup/Corporate Collaboration study82% of corporates say interactions with startups are important.

In support of promoting collaboration between enterprises and startups, impress.ai, an AI chatbot software for recruiters, participated in YourStory Start-up Dialogue. Sudhanshu Ahuja, CEO at impress.ai, was invited to moderate the panel of speakers at this event, which was co-hosted by YourStory and Asia PR Werkz, on Wednesday, 24 October 2018.

Topics covered during this event:

  • What are corporate partnerships?
  • Mistakes made by startups when trying to get corporate partnerships
  • How to deal with mismatch in expectations
  • Transformative effects of the right partnerships for both sides
  • How to prove your credibility
  • How to negotiate from a lower bargaining power
  • Being ready for a partnership — both for the startup and for the corporate

Panelists:

Ryan Lou, Fintech and Innovation Group, OCBC

Anurag Avula, Co-Founder & CEO, Shopmatic

Vipin Kalra, CEO, BankBazaar,

David Fowler, Director, PwC Singapore’s Venture Hub

Moderator: Sudhanshu Ahuja, CEO, impress.ai

Key takeaways and highlights:

What are corporate partnerships?

Anurag differentiated corporate partnerships into two types: A startup getting an enterprise as a customer versus a startup and an enterprise teaming up to build a symbiotic partnership to use each others strengths for mutual benefit.

He shared an example from Shopmatic, which has achieved this by securing distribution partnerships for its ecommerce platform for SMEs from large enterprises like HDFC and Singtel. Anurag also emphasized that the right incentives need be set at the operational level to make such partnerships work.

Mistakes made by startups when trying to get corporate partnerships

Vipin shared that it is very important for a startup to position themselves correctly when seeking any kind of partnership with an enterprise. He advised startups to really study how the enterprise makes money or what their needs could be and position themselves in the right place based on the enterprise’s needs. He also mentioned that it is important to show the big picture to the enterprise and start from there. Unless the enterprise can see the bigger vision, they won’t be able to see it as worth their time.

Ryan from OCBC Bank shared that startups should look for non-market leaders to partner with. For example, OCBC Bank is looking to partner with startups in markets where they are not market leaders, in places such as South East Asian countries. He also shared that it’s not helpful to think of startups as the competition. Competition is from challengers like Alibaba, Tencent, PingAn, and Grab who are challenging the status quo of the bank. So through partnerships with startups, banks have a better chance of beating the challengers.

Proving credibility

David from PwC shared that it’s very important for a startup to come across as credible when working with corporates. When PwC takes a startup to one of their customers, they are risking their own reputation on the startup’s credibility. He also shared that the partnership can be initiated both by an enterprise need as well as by a startup approaching them for a use case that could be useful for one of PwC’s clients.

How to deal with mismatch in expectations

Both Vipin and David shared that since the culture on both sides is different, it’s useful to have a third party helping both sides bridge the communication gap.

Transformative effects of the right partnerships for both sides

Both sides can massively benefit from a similar partnership.

How to negotiate from a lower bargaining power

Ryan and Anurag mentioned that startups needs to show that they have the right people in the team and know what they are talking about. Smaller businesses also need to make sure they comply with enterprise standards.

— — — — — — — — — — — — — — — — — — — — — — — — — — — —

Interested to learn how your enterprise business can collaborate with an innovative startup to improve hiring processes? Email contact@impress.ai today!

About impress.ai

impress.ai is an AI chatbot software for recruiters. Our conversational bots conduct competency based structured interviews using techniques from Industrial Organizational Psychology, specifically situational judgement questions. The chatbots autonomously interview, engage, and shortlist candidates at scale, 24/7, and actively fight human bias by hiding biasing information from human reviewers.

If you’re looking for one centralised recruitment solution to manage your growing recruitment needs, impress.ai’s AI-powered conversational bots can help make your day easier.

Our clients have experienced: 
– Upto 81% reduction in the time to qualify candidates 
– See Upto 30% reduction in the cost of hire
– 5X increase in reach

impress.ai is a Singapore based company and we work with several government clients as well as enterprises like DBS Bank, Accenture, and Singtel.

The New Digital Economy for HR: AI, Chatbots, and Blockchain: Co-hosted by CoQoons, Indorse, and impress.ai

Over 50 attendees came to learn about AI, chatbots, blockchain, and how HR is evolving.

impress.ai, an AI chatbot software for recruiters, partnered with CoQoons, a coworking space, and Indorse, a decentralised professional network on Ethereum blockchain, to co-host The New Digital Economy for HR: AI, Chatbots, & Blockchain on Tuesday, 28 August 2018.

Highlights of the event

The evening consisted of insights, use cases, and discussions about:

  • What HR professionals need to know about AI and blockchain
  • Digital trends and tools impacting the future of HR
  • How the HR role is evolving in today’s digital economy
  • HR case studies from Singapore’s most innovative enterprises

Speakers

Dr. Vaisagh Viswanathan (VT)

CTO and co-founder at impress.ai, VT is In charge of all things technology at the company. He holds a PhD in computer science from NTU and describes himself as a programmer, a scientist, a geek.

Gaurang Torvekar

CEO and co-founder at Indorse, Gaurang has been working in the Blockchain space from the last 2.5 years, and is considered to be a blockchain thought leader in South East Asia.

The Venue

CoQoons, subsidiary of Mapletree, is a coworking space that spans over 11,000 sqft of flexible work spaces such as hotdesking, window bars with sea view, height adjustable desks, private offices and meeting facilities. Boasting ‘One Location, Two Stunning Views’, our space offers unparalleled views of the lush greenery from Mount Faber and the blue waters surrounding Sentosa.

A big thank you to CoQoons and Indorse for co-hosting this event with us!

Interested to see how your team can experience:

– Upto 81% reduction in the time to qualify candidates 
– Upto 30% reduction in the cost of hire
– 5X increase in reach

impress.ai a well funded, Singaporean company and we work with 10 government agencies as well as enterprises like DBS Bank, Accenture, and Singtel.

Email contact@impress.ai to see a free product demo and learn more.

AI and the Power of Change: Co-hosted by impress.ai & Accenture

Over 300 gusts came to support the new partnership between Accenture and impress.ai.

impress.ai, an AI chatbot software for recruiters, partnered with Accenture, to host AI and the Power of Change on Thursday 16th August, 2018.

The evening consisted of insights, use cases, and panel discussions about:

  • The new partnership between Accenture and impress.ai
  • How AI is used to find talent and embedded across functions
  • Advice for aspiring data scientists to make an impact in their career

Highlights of the event

Speakers from Accenture Singapore spoke about how their team is using technology and analytics to find the right talent for their team. Using recruitment tools like impress.ai, they have launched a Digital Assessment Center where the emphasis will be less on a candidate’s CV and more on their experience and potential. Accenture advocates hiring in an ethical and fair manner while also bringing more women onboard to close the gender gap in the consulting industry.

Following the information sharing session, the panel discussion shared their advice for aspiring data science professionals.

Sudhanshu Ahuja, CEO and co-founder at impress.ai said, “Take AI out of the equation, instead talk about ROI, proof of concept, and proof of value. Then get the audience comfortable with your technology. They will not fully adopt it until they trust it. So, explain your technology in simple terms and once they understand the technology, then the impact will be exponential.”

Other panelists agreed that if analysts try to explain a model, people may feel lost. A good data scientist should focus on communicating what numbers mean and translating data into real business terms.

A key skill for data scientists to develop is presentation skills. Speakers suggested improving this skill by watching TED talks to see how other people present their thoughts.

One last piece of advice for aspiring data scientists includes understanding business challenges and focusing on using data to solve problems.

Speakers

Joon Seong

Joon Seong Lee is a Managing Director at Accenture Singapore. He leads Accenture Applied Intelligence, part of Accenture Digital for the ASEAN region. He has more than 20 years of in-depth experience in consulting with both local and regional clients across industries in the space of big data, analytics & artificial intelligence.

Grace Yip

Grace is currently the Head of HR for Accenture ASEAN and is a passionate human capitalist. She is one of the youngest females to be appointed Managing Director at Accenture in 2012. Over the last 5 years, Grace has published many articles across a variety of human capital topics in newspapers and HR magazines.

Tau Herng Lim

Tau Herng graduated with a B.A. in Economics and Statistics from UC Berkeley, and is currently a Data Science Consultant with Accenture’s Data Science Centre of Excellence in Singapore. He has worked on projects for clients in the public sector, and financial services industries, covering marketing analytics, predictive policing, predictive asset maintenance, and predictive model operationalisation and management.

Norhafishah (Ifi) Malek

Norhafishah is a Principal Director at Accenture Singapore and currently leads the Accenture ASEAN Digital Solution Design team. She has 14 years of consulting experience working with industry leaders and analytics enthusiasts.

Xavier Conort

Xavier Conort is a rock star in the data science community and has been ranked the #1 data scientist on Kaggle, the most popular online data science competition platform.

Sudhanshu Ahuja

CEO and co-founder at impress.ai, he currently manages sales, fundraising, and vision at the company. Sudhanshu is an entrepreneur, a go-getter, a trailblazer, and an NTU alumni.

Interested to learn how AI can help your recruitment team improve processes?

Email contact@impress.ai to find out how your team can experience:

– Upto 81% reduction in the time to qualify candidates 
– Upto 30% reduction in the cost of hire
– 5X increase in reach

impress.ai a well funded, Singaporean company and we work with 10 government agencies as well as enterprises including DBS Bank, Accenture, and Singtel.