Integrating generative AI with other AI models and applications can enhance their capabilities and create more comprehensive and effective solutions. Here are several ways this integration can be achieved:

1. Natural Language Processing (NLP):

• Chatbots and Virtual Assistants: Integrative generative AI can create more human-like and contextually aware responses, improving user interaction and satisfaction.
• Text Summarization and Translation: Combining generative AI with existing NLP models can improve the accuracy and fluency of summaries and translations.

2. Computer Vision:

• Image Generation and Enhancement: Generative AI can be used for creating high-quality images from text descriptions, improving image resolution, and filling in missing parts of images.
• Object Detection and Recognition: Integrating generative models can help in generating synthetic data to train and enhance object detection models.

3. Healthcare:

• Medical Imaging: Generative AI can enhance medical images, assist in creating synthetic medical data for training purposes, and improve diagnostics by integrating with existing imaging analysis models.
• Personalized Medicine: By generating patient-specific simulations and treatment plans, generative AI can assist in precision medicine efforts.

4. Finance:

• Fraud Detection: Generative models can simulate fraudulent transactions to improve the training of detection algorithms.
• Financial Forecasting: Integrating generative AI with predictive models can enhance scenario analysis and risk assessment.

5. Entertainment and Media:

• Content Creation: Generative AI can assist in creating music, art, and writing, augmenting the creative process and providing new tools for artists.
• Game Development: It can be used to create characters, dialogues, and scenarios, enhancing the gaming experience.

6. Education:

• Tutoring Systems: Combining generative AI with educational models can create personalized learning experiences, generating tailored content and feedback for students.
• Content Generation: Automating the creation of educational materials, such as quizzes and study guides, based on curriculum data.

7. Robotics:

• Behavior Simulation: Generative AI can simulate various robotic behaviors in different scenarios, improving the robustness of robotic models.
• Human-Robot Interaction: Enhancing the interaction by generating more natural and context-aware responses from robots.

8. Data Augmentation:

• Training Data Generation: Generative models can create synthetic data to augment training datasets, improving the performance of machine learning models.
• Anomaly Detection: Generating normal behavior patterns to help identify deviations and anomalies more effectively.

9. Personalization and Recommendation Systems:

• Content Personalization: Generative AI can create personalized content recommendations based on user preferences and behavior.
• Dynamic User Interfaces: Generating adaptive and personalized user interfaces that change based on user interactions and preferences.

Integrating generative AI with other AI models and applications requires careful consideration of data quality, model training, and ethical implications to ensure the effectiveness and reliability of the integrated solutions.

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Since the time chatbots have entered the advanced world, every organization and marketer are interested to utilize them as a significant tool to interact with their clients on a daily basis. Some of them were sufficiently quick to try things out, while others are still at the thinking stage. Brands can connect with their customers and interact with them in a personal manner by means of chatbots.

With the capability of chatbots to give client support more than ever, brands can now increase their sales. Subsequently, chatbots can provide opportunities to improve brand engagement, assist organizations with accomplishing business growth, and make monetary profits. Businesses as well as customers are cherishing this innovation.

The problem of waiting for long periods of time to connect with customer care executives gets wiped out. In addition, chatbots can provide solutions to clients in any event, even during non-operational hours.

Because of chatbot’s brief answers and 24*7 accessibility, 69 percent of customers today favor communicating with chatbots as opposed to people. Hence, chatbots have become an absolute necessity for organizations to survive. Initially, when chatbots were new, they failed to lead discussions.

Today, chatbots have developed to become refined and sophisticated models. In any case, chatbots sometimes despite everything come up short on understanding the client’s expectations and language. They should, in this manner, be trained well to comprehend the specific situation, user intent, and sarcasm in human language.

Artificial intelligence plays an important role in increasing the efficiency of chatbots. Artificial intelligence gives a human touch to each discussion chatbot strikes. The bot comprehends the customer’s inquiry and triggers a precise response in the same manner in which humans can understand each other’s concerns and give a reaction accordingly.

Chatbot with AI capabilities makes your bot capable and clever to answer complex inquiries. The communication is engaging, conversational, and lively. Chatbot learns from each discussion it has with the clients. It analyses the past interaction to improve the current response. This movement assists with improving the proficiency of bot reaction.

In addition, it helps to understand your client’s choices and preferences. Smart conversations spare customer’s time by helping them to locate the correct data and address their queries. Machine learning is an algorithm that causes the chatbot to learn from questions and the information given by organizations during bot training.

At the point when a query is triggered, machine learning encourages the bot to initially screen the previous discussion it had with the client and give a response accordingly. Along with AI and machine learning, NLP also plays a major role in revolutionizing chatbots. NLP assists organizations with offering a pleasant experience to customers.

With regards to chatbots, NLP can be utilized to recognize what the client is really attempting to tell or inquire about. Along these lines, brands can interact with their clients in a personal, more sympathetic way, which can at last make them stand unique among their competitors. NLP systems widely use machine learning to parse client input in order to take out the important elements and comprehend client intent.

Chatbots with natural language processing can parse numerous client messages to limit failures. When it comes to natural language processing, designers can train the bot on numerous interactions and discussions it will experience as well as giving various instances of content it will interact with as that will in a general sense give it a much more extensive scope with which it can additionally evaluate and decipher inquiries more adequately.

Businesses should train chatbots to switch their tones, from formal to casual, to keep customers engaged and intrigued. Be that as it may, to lead such human-like discussions, chatbots must have a profound context-awareness ability. Furthermore, for that ability, designing chatbots with NLP is fundamental.

With NLP, chatbots can without much of a problem comprehend the mind-boggling human language. Each individual possesses a different style while communicating. With NLP, chatbots can rapidly understand an individual’s personality and react in the same manner. Moreover, chatbots can understand sarcasm, humor, and other conversational tones better with NLP. Truly, NLP gives chatbot their very own personality.

With computational algorithms, context extraction, content summary, and sentiment examination, NLP can help chatbots decipher the raw content, process it, and convey enhanced data to clients. Natural language processing assists with understanding and deciphering customer requests, difficulties and issues, and then utilizing an advanced level of AI to help convey the suitable actions to fulfill the client’s needs.

Advanced NLP can even analyze the meaning of a client’s messages. For instance, if you are making an inquiry or saying something. While this may appear to be unimportant, it can deeply affect a chatbot’s capacity to carry on an effective discussion with a user.

While natural language processing positively can’t produce miracles and guarantee that a chatbot appropriately reacts to each message, it is incredible enough to become the deciding factor in a chatbot’s prosperity. It’s important to not think little of this significant and often ignored part of chatbots.

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Artificial Intelligence is redefining how we look at technology and use it, especially the mobile app industry. A lot of people have used this technology to improve the engagement level within the app, and increase the conversion rate for the business. We don’t have an Iron Man-like mobile app as of now but, we are constantly progressing towards making apps revolutionary, usable, and predictive. We are using predictive analytics’ engine, and other coding methods to enhance the mobile apps and make them more experiential.

There are many ways in which Artificial Intelligence has enhanced the mobile app industry. Here, we will take you through some of the ways in which the apps have been revolutionized and transformed with mobile apps.

1.     Personalization of Mobile Apps

Inspiring minds and influencing people can help enhance engagement. However, to make sure you are able to inspire the right minds, you ought to have insights that cater to their thoughts and help you understand them better. As a result, it is important for you to incorporate Artificial Intelligence into your apps.

This technology has transformed the way users use mobile apps, and engage with them. AI with deep-rooted learning techniques can easily understand what goes into a user’s mind, and mine the insights that help you offer better recommendations and a more personalized screen.

Netflix, which is a popular streaming platform, uses AI to help recommend programs to its viewers. This streaming platform tends to record the past views of the user along with their natural preferences. ML an integral part of AI, records these aspects, runs an algorithm to understand what the viewer likes most.

It then recommends programs based on their history and preferences. This personalization helps the user stay on the app for a longer time, and enables better engagement and conversion.

2.     Better Sales Forecasting

Want to know what will be in demand this season? For a long time, the one thing that most salespeople have been unable to define or properly manage is the demand. We are hardly aware of how the demand changes or evolves for the new year.

However, with Artificial Intelligence tied to your mobile app, you can easily understand the demand for a particular product. You will also be able to understand the demand for a new product you are going to launch. Let’s take a look at the how before we understand any further.

With sales, you are immediately turned to the number of the particular product that will be sold in a go. The forecasting for this particular number is quite difficult. Artificial Intelligence, in case of a known product, looks at past sales figures. It understands why the sale happened when it happened and how it converted into a sale.

Similarly, it will also look at demographic patterns for the sale and other aspects. Immediately, an Algorithm is built which helps forecast the sale for the product in the coming times. It will help understand the demand, which in turn will allow you to keep up with the inventory needs.

In the case of a new product, the trend of the product is observed for a period of a few days before deriving with finality the forecast for its demand.

3.     Retail Assortments

When you apply AI to retail, you will see new store layouts and a better understanding of the placement of the products. How? When you enter the store, there is a specific way in which you purchase. This is true for online stores as well. That’s why Artificial Intelligence can help you. it will help you understand the exact way in which users tend to shop online/offline, and will offer to design the layouts accordingly. for instance, if the shampoo is placed next to oil, there is a good chance that you might be able to convert both products, and gain more profits.

The idea is to understand the methods and develop an algorithm that will connect your customer’s purchase behavior with the way they complete the purchase. What gets them engaged with the store and how they route their shopping?

4.     Extends Customer Support

Artificial Intelligence can help small businesses and enhance your customer service. With Chatbots, you can easily connect with the users, with fewer resources and that too in real-time. bots will represent your customer service executives, and help people complete their needs.

For instance, if someone has a query, and your executives are running busy, then you can get the bot to engage the person for a while. In case these questions can be answered by the bot, you will not only be saving the resource’s time but also saving a lot of your money

In the case of small businesses, it is very time consuming and money intensive to hire resources who can understand your needs, and offer help to the customers immediately. However, you can avail of the bot service, which helps in connecting with the customers immediately and get you the much necessary support.

5.     Fraud Detection

For many companies, safety and security play an important role. If your customers don’t feel that you are safe enough, they may not even consider you for their transactions.

Security also needs to ensure that anytime a fraud is likely to occur, the system should detect, and immediately report. This is not possible without technology. That’s why you need to implement Artificial Intelligence, as it will detect fraud immediately, and help you connect with the customers and report the same.

Any fraud that happens in the transactions will be immediately reported, and you will be able to safeguard your business against fraudsters and make the place safe and secure. The algorithm will match with the customer’s transaction habits, and immediately report any haywire transaction.

6.     Real-time Decision Making

With the Internet of Things associated with Artificial Intelligence, you will be able to get real-time data from all the devices connected with your business. for instance, the businesses operating in the manufacturing industry would be able to understand the data that is needed from the shop floor and get it immediately through the connected smart sensors. Artificial Intelligence will be able to apply algorithms to this data and gather insights. all this happens in real-time, which helps businesses make real-time decisions essential for better business growth.

7.     Improved Search Experience

With fewer keywords and better keyword analysis, the online stores and businesses should be able to offer key search results that match the needs of the user. For instance, if the user types a wrong spelling, even then the search engine within the app should be able to detect the right spelling and offer the results accordingly.

For this purpose, you need AI which will study all the wrong keywords and ways in which the user searches for a particular product. When you are more than aware of the search methods, it becomes easy for you to create an algorithm that will enhance the search results.

The idea is to make sure that the user is not disengaged from the app, and the app provides them with the results they are looking forward to, despite the keywords they enter.

Summing Up

Artificial Intelligence will ramp up the mobile apps and will ensure better user engagement within the mobile apps. With businesses incorporating AI within mobile apps, it will surely be a good start for them, as it will enhance user experience and will result in more conversions.

The idea is to understand how exactly AI fits into your organization, and how you can use it to fulfill your needs. Once the requirement analysis is done and you have an algorithm ready, get started with incorporating AI into your mobile app, and see how your app grows.

The post 7 Ways Artificial intelligence is Revolutionizing the Mobile App Industry in 2020 appeared first on Artificial Intelligence.

AI is fast progressing in every field like healthcare, manufacturing, law, finance, retail, real estate, accountancy, digital marketing. Every field is being computational and becoming more advanced with some remarkable capabilities emerging these past years.  Artificial Intelligence is reshaping the economy and career landscape with a wide range of diverse patterns from autonomous systems, chatbots, document classification to advanced predictive analytics solutions. Albeit most of the problems faced are in terms of driving down costs, removing friction, speeding processes up, and improving efficiency that can be mitigated as the machines are becoming smarter day by day.

Use of  knowledge graphs in professional services

Google introduced a newer type of database called the knowledge graph in the year 2012. This type of database are compatible and multiple databases can be interrogated simultaneously. Knowledge graphs link triplets of information’s subject, object, and the relationship between them. This flexible approach allows us to get precise answers to rich and complex questions. 

Problems with knowledge graphs are that they are time-consuming, and expensive to populate. This problem can be mitigated by the rapid improvement in AI called natural language processing, which enables knowledge graphs to be populated automatically. The use of knowledge graphs in professional services like accountancy and law would greatly improve and speed up the work as data retrieval is automated. 

Reinforcement learning: the next big thing of AI

“Reinforcement learning” is a classic behavioral phenomenon known as psychology literature in the year 1950s, said Dr. Matt Johnson who is the professor of psychology at Hult Business School and the author of the Blindsight: the (mostly hidden ways marketing reshapes our brains).

According to this theory, the agent comes in contact with the surrounding environment and observes a particular activity which then responds to the results depending upon the surrounding.

AI-powered characters will adapt to produce elaborate storylines, and consumers will no longer be confined to fixed dialogues and rigid interaction between non-player markets.

The AI doctor might try medications almost randomly to see what effect they have, and overtime should learn the patterns. and understanding of which medications work best in which situation. 

Dark matter: Turns AI understand images like humans

The scientists at Massachetrus Institute of Technology and the University of California, Los Angeles, argue that the key to making AI systems is about visual data like human AI to address “dark matter” of computer vision, the things that are not visible in pixels.

AI in content marketing

AI is a  dynamic game-changer for digital marketing from 24/7 chatbots, analyzing data and trends, custom feeds to generating content. AI recommends content topics that align with the trending topic. AI recommends SEO strategies for more relevant and valuable content. AI is creating custom, personalized content for buying users at each stage of customer experience.

The chatbots provide real-life customer experience so they don’t have to fill the generic form. This provides users quick and easy answers to their questions for their immediate purchase. Users feel they are having a real conversation with humans while it’s a robot.

Conclusion

AI is becoming affordable and accessible for any software developer. The tech giants are currently competing to dominate the field of artificial intelligence. AI is a necessity in the year 2020 that will witness a growth in facial recognition, computer vision, autonomous vehicles, automatic text generation, cloud, AI-enabled chips, and privacy and policy.

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Chatbots and virtual assistants that don’t provide the right answers to customer queries can result in a frustrating digital experiences for customers – particularly those chatbots programmed without deep learning capabilities.

Deep learning is essential for automated chatbots to understand natural language questions and to provide the right answers, which is something that AI-powered search firm Lucidworks has taken on board. The company recently launched Smart Answers for chatbots and virtual assistants – a solution the company says will help to avoid frustrating digital support experiences and long customer support wait times.

According to Lucidworks, companies rely on digital portals to provide information to users, whether digital commerce customers looking for product information before purchase, employees hunting for an HR document, or someone looking for an airline’s updated cancellation policies. Information is often scattered across disparate silos and is impossible for a user to locate using natural language questions.

Smart Answers on Lucidworks Fusion aims to help employees and customers resolve issues via chatbots or virtual assistants without the need for additional support or ‘irrelevant’ search results.

Lucidworks CEO Will Hayes explains that customers expect more conversational interactions with a chatbot or virtual assistant that understands natural language questions, and is quickly provides the correct answers. 

“In the current environment, it’s important to meet customers where they are, especially if they’re moving from a real life experience to digital,” he says.

“Our work over the years with Fusion has been focused on understanding a user’s intent. Digging for answers wears their patience, wastes their time, and can even motivate them to seek out a competitor. Being able to understand what your users are asking for in their own words and returning the best answer instantly, allows companies to provide a natural conversational experience digitally. With Smart Answers, we’re cutting down time-to-resolution, increasing customer retention, and powering conversational experiences for users.”

The company cites Red Hat as one of its customers.

“We conducted an A/B test where we introduced a self-solve based homepage to some customers. There was an increase in traffic that confirmed that customers are really motivated to self-solve and we saw a seven per cent decrease in support case creation for customers who were given the self-solve homepage,” comments Red Hat principal software engineer Manikandan Sivanesan.

Lucidworks states that Smart Answers on Lucidworks Fusion enhances conversational applications to help users help themselves by delivering immediate and contextual responses that drive engagement and satisfaction.

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What’s in store for all of us in the future is that artificial intelligence (AI) in some form or other is here to stay. In all aspects of our lives. There might be robots at home to help us with chores instead of maids and of course, there will be plenty of AI help in our workplaces. How invasive or pervasive it will get is not predictable. But this market is projected to reach $70 billion by 2020.

Currently, AI is being used in the form of chatbots, digital assistants and machine learning. These are used for assisted intelligence (GPS in cars), augmented intelligence (as used by the likes of Uber, Ola) and autonomous intelligence (driver-less cars, home cleaning robots, etc).

The hope is that these work-in-progress technologies and the ones that are just a pipe dream so far but may become a reality in the future, will free up valuable time for human beings to do more cutting edge work – give them the mind space to think deeper, make better decisions with the help of data generated by AI, and become more creative and imaginative.

What AI can also do is not just fancy hi-tech work. It can do the low-tech stuff too and “has the potential to democratise services like education, law, and financial advice, providing them to everyone in a personalised manner and at a lower cost”, stated a PwC report.

Healthcare sector to benefit the most

Among the 2,500 consumers and business decision-makers surveyed in the report, 63 percent of them feel that AI will benefit mankind and help solve complex problems. Up to 59 percent feel it will help people live fulfilling lives. Some 46 percent feel that it will take away jobs and only 23 percent feel they will become movie-style monsters without hearts that go on a rampage against their human creators. Eighty-seven percent fear that their privacy will be at risk.

But it’s in the healthcare sector, where AI will prove hugely beneficial to all, irrespective of income. It’s already successfully identifying “autism in babies with 81 percent accuracy and skin cancer with 91 percent accuracy. There’s more – as people feel that “AI assistants will be replacing humans as tutors (58 percent), travel agents (56 percent), tax preparers (54 percent), and office assistants (52 percent).” But they are not sure about adopting them as financial advisors, doctors, chauffeurs and house cleaners just yet. 77 percent of the people polled said they still want a human doctor and 61 percent wanted a human teacher, just to keep that human touch in some aspect of their lives.

However, AI is being used in creative ways already. A DoNotPay bot appeals parking tickets for free and Ayannah is a credit scoring service that has provided 87 percent of poor Filipinos with a credit score that they wouldn’t have got because they did not have bank accounts. The RIVA Machine is a robot that fills prescriptions, hence giving pharmacists more time to discuss medications and side effects with their customers. The fact is that what most people consider ideal today is the best of both worlds – 43 percent of millennials and 28 percent of business executives would pay a premium for a hybrid service that has AI along with a human being’s helping hand.

PwC Innovation Lead, Data and Analytics, Anand Rao, said in the report, “In the last few decades, we as mankind have made our systems much more complex. As a result, no one person can cumulatively know what is involved in any given system or solution. Our machines are becoming smarter by learning and embodying the collective experience of mankind, or a group of experts.”

Go along with the wave

So, don’t fight this technological wave, instead, go along with it and the ride might just become super interesting. The reality is that not a lot of business heads are taking this trend quite as seriously as they should. (Graphic: AI2) But if they want to begin somewhere, here’s what they need to do, to be ready for the future:

Make AI operational across business functions and units 24/7.

Currently, business leaders are complacent about risks and need to start becoming responsible about them.

Reinvent your business model and look for opportunities.

Start with the first step: Get on board the AI game. This year’s PwC’s third annual AI Predictions report stated that only 4% of the executives surveyed plan to deploy it enterprise-wide in 2020. Last year, this figure was 20 percent!

Cultivate adaptability and creativity – a sense of wonder and curiosity will also help

Embrace diverse perspectives and collaborate.

On a lighter note, survey respondents felt that by 2025, AI might be able to come up with a top 100 Billboard song, write a hit TV series or create a piece of art that is worth over $100,000. However, AI was unlikely to come up with a New York Times bestseller, writing an Oscar-winning movie and winning a Pulitzer Prize for journalism. It was heartening to note this last point, for sure!

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Technological progress in today’s society has reached unprecedented levels; the World Wide Web did not even exist thirty years ago, while smartphones as we know them today have barely been around for a decade. Now, an even more sophisticated tool is at the forefront of changing the way we live – Artificial Intelligence (AI).

McKinsey’s Global Institute model predicts that approximately 70 percent of companies will adopt some form of AI by 2030, and that countries which are able to establish themselves as AI leaders could capture up to 20 to 25 percent more economic benefits than current levels. In recent years, one particular use of AI has become a point of contention – the use of AI in recruitment.

AI in Recruitment – What Does it Entail?

AI has been said to be the future of many things – and recruitment is no exception. Recently, HR professionals have been increasingly looking at AI to automate and optimize the recruiting workflow, which has allowed recruiters to focus their time on more value-adding tasks. Below are just a few examples of how AI in recruitment has increased efficiencies and led to better job matches.

1. CV screening: Based on factors including the skills and experience required, AI may be used to efficiently sort and select candidates based on their CVs. This has meant more efficient talent sourcing and matching, and the rediscovery of talent from past applications.
2. Improving the candidate experience: AI can be programmed to provide real-time feedback to candidates, thereby reducing recruiters’ workloads and minimizing candidate frustration.
3. Removing implicit biases: Purported to rid hiring practices of human biases, AI has been said to be able to focus solely on the skills and experiences of candidates, thereby supporting a more diverse workforce.

However, as alluring as it may seem to use AI in recruitment, it is important to recognize its potential pitfalls. In the oft-cited example of Amazon, who unintentionally built an AI recruitment software which discriminated against women, it is clear that as good-intentioned as these AI program may be, there are also dangers to using AI to hire employees, who are the backbone of any company. These include:

1. Overlooking atypical qualities and experiences: Should AI prioritize a candidate who has taken on multiple responsibilities in a lesser-known company, or one who has interned at a Fortune 500 company?
2. Program limitations: AI software is not written by itself; a program may only be as good as it has been programmed to be, and understand as many scenarios as it has been taught.
3. Learning human biases: As in the case of Amazon, machines can learn the implicit biases of humans and amplify them in every decision that it makes.

The key, therefore, is in achieving a delicate mix between artificial intelligence and human intelligence, as even the most sophisticated software in the world would not be able to learn the human instinct a HR professional might have for the right candidate. And this would be even more so for an industry as focused on human connections as hospitality.

AI Recruitment in Hospitality

As hotels become social hotspots and luxury becomes more about the experience than the indulgence, the hospitality industry has become more reliant than ever on finding the right talent to serve the corporate values and live out its tale of service excellence. Yet, talent acquisition remains one of the key challenges of the hospitality sector, plagued by the common misperceptions of working in the service industry. This underscores the importance of matching the talent that do come through, to the right brand and position – and AI is increasingly being put forth as that Holy Grail.

What if an AI program could accurately tell you that your next candidate has a high likelihood of performing well in your company, and that he would best fit in a Kimpton Hotel rather than an InterContinental – even before he has stepped into the interview room? The InterContinental Hotel Group’s (IHG) predictive technology has been one of the first on the hospitality scene, similar to Hilton’s Ally, which has been used to automate recruitment for their contact centers.

At the same time, person-job misfits often occur because candidates themselves do not understand which kind of workplace environment would suit them best; neither does it help that we live in an era of simply sending out five-hundred copies of your resume and hoping that you hear back on one of them. This is an issue which Marriott International’s Marriott Careers (MC) chatbot could tackle, through features such as a quiz which helps potential candidates understand which of its thirty brands would best fit them.

Yet, the possibilities of AI do not simply end there. For multinational brands, AI-programmed recruitment practices could mean the ability to re-allocate strong applicants to relevant (and perhaps better-suited) open positions elsewhere in the world, thereby allowing such brands to retain talent in the company. There is also potential for AI to make employment a two-way street; rather than only looking at the competencies of candidates, AI could enable us to assess the profiles of our current employees, identify the gaps, and hire specifically to fill those gaps. This could mean a better-rounded workforce which is better able to cater to different situations and guests’ needs.

The hospitality industry is becoming increasingly focused on personalization and customization, and it seems that the hospitality recruitment sector too is jumping on this bandwagon – perhaps we could one day filter through open positions based on our personalities and ambitions?

Predicting the humanness in humans – or taking the human touch out of hiring?

With the far-reaching capabilities of AI, one may wonder if it may be used not only to predict the future performance of a candidate, but also to transform the hiring process. Many recruiters today emphasize hiring for attitude rather than skills, but it is not always easy to walk the talk when hiring decisions can become so subjective. Could AI thus be programmed to determine if we should take a chance on a less-experienced hospitality graduate with the right personality and all the enthusiasm in the world, over an average-performing applicant who already has two years of industry experience?

While the use of AI may take a while to become the norm in hiring, it is not difficult to imagine the implications of having fully automatized CV-screening processes. ‘Machine learning’ equates to codes and formulas that can be learned by humans – which means that it may not take long for someone to crack the code and begin producing ‘AI-optimized CV templates’. Ironically, this could also mean taking the creativity and personality out of the individualized CVs that applicants need to have now, in order to catch a recruiter’s eye.

From an employer’s perspective, interviews are also an opportunity for hiring managers to ‘connect’ with potential employees, and to understand and assess situations in ways that a machine may not be able to. It is also important for potential employees to feel sufficiently valued, for the company to take the time for a face-to-face interview rather than simply be put to talk to a machine; for an industry built on creating human relationships, it would seem almost a tad ironic to rely on a machine to assess the suitability of a candidate for its demands. Nonetheless, these managers more than likely possess the one thing that AI seeks to eliminate – implicit biases. An AI may lack that human touch, but never has a human been a hundred-percent flawless either, so where should we draw the line?

The use of AI in recruitment still lies in the testing stages, with many HR professionals and candidates alike expressing skepticism towards the reliability of such software. Perhaps AI could simply be used to ‘cold-sort’ candidate profiles and improve efficiencies, while interviews and final decision-making processes lie with the hiring manager; after all, artificial intelligence should support, not replace human intelligence. As these programs continue to evolve, it would also be interesting to think of AI not just as a tool to make our lives easier, but as a stepping-stone to potentially change the way we hire and how we see value in a candidate’s skills and attitude.

AI: Our Tomorrow?

The use of AI in recruitment is no temporary phenomenon. As the hospitality industry continually seeks to automate and streamline its processes to drive operational efficiencies, AI-automated hiring practices may soon become a necessity. This means that perhaps sooner rather than later, you may see your CV being screened by an AI software (if it isn’t already), or find yourself in a video interview, where your language and facial expressions are being analyzed by an AI.

While this prospect of having your every word or twitch of an eye examined by a machine may seem almost dystopic, we have evolved immensely from when the first online job platform was created twenty-five years ago. Today, LinkedIn has made our professional lives a continuous self-marketing process; everything you say or do professionally is already being scrutinized by the online community – so could AI be our tomorrow?

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If you’ve ever watched a robot science fiction movie, odds are good you have seen one where the robots try to take over the world. However, if this is your idea of what artificial intelligence is in the real world, maybe it’s time we separate fact from fiction and discuss the reality of AI today.

AI and automation are being used for tedious manual and repetitive tasks, saving companies the cost of hiring employees. AI also helps to improve human decision-making (we need a little help in this area) by using algorithms to solve problems.

Here are a few ways AI will help us improve the workplace in the very near future:

Candidates can find a better fit: Rather than parsing through hundreds of jobs that aren’t the perfect fit, people looking for jobs can use AI to personalize their job searches and focus on the ones they’re qualified for. At IBM, a tool called “Watson Candidate Assist” lets applicants enter their skills to customize the jobs they can apply for.

The training process is improved: Typically, established employees are asked to train new hires, which takes them away from their regular responsibilities. But thanks to technology, new employees can learn from AI coaches who are available throughout the onboarding process, which keeps disruption in the workplace to a minimum.

Ongoing training gets easier: AI improves creativity and learning by personalizing each training experience based on the specific learning patterns of each student. Chatbots will facilitate training, and the company benefits by having employees who are always on top of the latest software, tools, and strategies to do their jobs well.

Productivity will skyrocket: AI will help us save time by scheduling meetings automatically, analyzing large amounts of data, and answering commonly-asked questions. Tools like chatbots can respond to customers’ questions about store hours, products, and shipping policies, removing the need for an actual human to do that task. Replacing simple tasks with technology frees up actual employees to focus on more important work and cuts down on labour costs.

You can decrease workplace stress: The American Psychological Association reports 64% of Americans experience work-related stress. AI shows promise when it comes to well-being technology that can monitor stress and health, like a Fitbit type tool. These cloud-based well-being technologies also can be integrated into an organization’s wellness program to help reduce sick days.

Employees will stay at companies longer: Employees are staying in positions up to 30% longer than they used to. Because of this, some companies are trying to take an active role in helping employees focus on growing their career experience using AI and machine learning to train employees for that next step up the corporate ladder.

Industries facing disruption

A common misconception is that once AI becomes commonplace, jobs will be eliminated and replaced by robots. According to Gartner, by 2020, AI “will actually create more jobs than it eliminates.” However, some industries will change more than others.

Some industries that can expect disruption from AI include:

• Call centers/retail: Chatbots are able to answer repetitive questions in seconds, leaving trained technicians to answer more advanced queries online.

• Manufacturing: Manufacturers are using AI to improve automation and optimization. They are also applying artificial intelligence algorithms to augment decision-making.

• Agriculture: Agriculture is suffering from labour shortages and could benefit from more automation and efficiency. AI could help strengthen the industry.

• Energy: AI will be helpful in several areas of oil and gas, including tracking tankers to predict what has been shipped, arrival times, and more. This can help traders make better decisions.

• Healthcare: AI and automation may help to eliminate diseases. There have already been some great advances that provide more accurate diagnoses, cures, and disease prevention.

Preparing for the AI revolution

By 2020, the Fourth Industrial Revolution will bring us artificial intelligence, machine learning, advanced robotics, biotech, and more. According to McKinsey research, fewer than 5% of jobswill be fully automated, and 60% of jobs may have around 30% of their activities automated. As these advancements change our work and lives, they will cause some jobs to disappear, but also create new jobs that don’t exist today. The workforce of the future is going to have to align its skill sets to keep up.

The key is being open to innovative ways that technology can improve the workplace. Yes, it takes a ramp-up to adapt to these changes, but in the long run, they’re going to revolutionize the way we work. HR managers should look for people who either have experience using technology like AI or who are open to learning how to apply it to their role.

Artificial intelligence is coming, whether your business is ready or not. It’s time to get ready for this phenomenon and find ways to leverage it . . . or you just may end up being left behind.

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They’re called salespeople, but they spend shockingly little of their time selling. Instead, their days consist of administrative work, manual data entry, looking for potential customers and communicating with those prospects: cold calling, sending emails, scheduling meetings and having conversations — many of which lead to nothing.

This is both time-consuming and expensive for companies. Lost sales productivity and wasted marketing budgets cost organizations $1 trillion dollars a year, according to industry estimates.

Things are starting to shift, however. New tools, including ones that incorporate artificial intelligence (AI) — mostly machine learning and natural language processing — are changing the ways in which salespeople do their day-to-day jobs.

For all the talk about how AI is revolutionizing the business-to-business (B2B) sales process, its biggest advantage is more mundane: It is helping salespeople better manage their time.

AI is a transformative technology. Its power lies in its ability to extract, parse and analyze massive amounts of data almost instantly. In a sales context, AI-enabled tools help B2B marketers gain a more nuanced understanding of their customers’ wants and needs and improve efficiencies like never before.

According to research from McKinsey & Company, organizations that use AI in sales cite an increase in leads and appointments of more than 50per cent, cost reductions of 40–60 percent and call time reductions of 60–70 percent.

Interestingly, the most innovative tools are also the most practical. Today’s AI-powered software does everything from write emails to schedule meetings to detect sales behavior. This helps salespeople identify viable leads and close more deals.

Take, for instance, chatbots. Chatbots use AI to conduct conversations via video, audio or text. Chatbots begin the sales process by asking customers basic questions related to their role, industry and company size.

These low-level questions weed out those who may not meet the minimum qualifications of a company’s prospect profile. No salesperson wants to waste time in a conversation that’s not going anywhere.

Chatbots and lead scoring machine learning tools further improve and enhance the sales process. Lead scoring determines the worthiness of potential customers by attaching values to them based on their interest in a given set of products or services.

Scores not only help salespeople spot potential customers more quickly, they also help salespeople customize their pitches by mapping out an individual prospect’s needs.

That’s not all. Virtual sales assistants and chatbots can arrange meetings and calls, which drastically reduce the amount of back-and-forth scheduling details that often swamp salespeople.

Intelligent predictive engagement tools are another illustration. These AI-powered tools remind salespeople to reach out to prospective customers and even recommend what to say during that follow-up call or email. After all, the key to any follow-up with a client is relevant and meaningful content.

Finally, there’s process automation. Automation, along with predictive analytics, helps identify relationships between pieces of data. This allows salespeople to develop a deeper understanding of customer behavior and helps them forecast future sales more accurately.

Prescriptive analytics, meanwhile, helps salespeople navigate the sales process by uncovering the best path to value for customers, according to a recent research report by Gartner. Put simply, it enables salespeople to adapt and customize their product recommendations based on their customers’ individual needs.

These AI-powered tools are geared at improving sales productivity. They eliminate tedious busywork, such as logging calls or taking notes, and allow salespeople to focus on the essential parts of their job.

Importantly, they empower salespeople to engage with customers who are most apt to buy their products and services.

To be sure, just because these new tools exist does not mean that salespeople will embrace them. Case in point: A large number of customer relationship management (CRM) implementations fail because salespeople do not want to use their time doing data entry. (They, understandably, prefer to spend their time selling.)

However, these data inputs are vital to helping salespeople derive value from CRM by generating the kinds of insights necessary to improve their product’s attractiveness in the market and increase sales. To realize the value of CRM systems, salespeople need to be persuaded that adopting them is worthwhile.

There’s the rub: Given the biggest constraint for salespeople is the availability of “precious selling time,” organizations need to show salespeople that AI implementations can help reallocate their time toward selling. This provides the best opportunity to prevent AI tools from going the way of CRM systems.

But it’s likely that salespeople will need convincing. The value proposition is clear: Adopting AI tools will give them their time back.

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Today’s workplace is becoming more efficient thanks to the effective implementation of technology. Between new collaboration tools, the incorporation of artificial intelligence (AI) and better platforms for connecting with customers, the way we work has changed greatly over the last couple of decades.

As companies look for new ways to stay ahead of industry changes, special attention needs to be directed toward how things like AI can better support administrative objectives rather than carrying out repetitive tasks that can take away beneficial time from employees. We’re starting to see artificial intelligence augment and enhance the human element, rather than replace it, to achieve greater results.

In a PwC survey conducted last February that sampled 2,500 consumers and business decision makers, 67% of business executives believe leveraging AI will amplify human intelligence and allow for more high-level thought, creativity, and decision making by allowing us to better process and analyze the constant increase of data in today’s world.

Let’s identify how businesses are already starting to set themselves apart by integrating AI and machine learning into millennial-minded organizations.

AI-Powered Chatbots Are Transforming The Employee Experience

Chatbots are like personal assistants for employees, providing access to information from multiple data sources instantly. Machine learning continuously expands chatbots’ knowledge bases, driving automation, operational efficiencies and scalability as a company grows. Your artificial intelligence is only as good as the data it can access.

For example, Virgin Atlantic rolled out Facebook’s Workplace last September in an effort to improve information sharing between staff and senior executives at the company. Workplace is an instant messaging platform, but it features bot integrations. Chatbots can serve as a reliable tool to help bring employees and management together and serve as an extension of the HR function.

Integrating chatbots with scheduling applications, HR management solutions, intranet sites, CRMs, and other systems empowers employees to make better business decisions and increases productivity by reducing time spent wasted looking for information.

Artificial Intelligence Improves Customer Experience by Improving Employee Experience

Just like your employees, customers are inundated with information on a daily basis. To stay competitive, companies have to understand the needs of discerning customers, and provide near perfect customer experiences to win over new customers and retain existing ones. Rather than anticipating customer demands, having access to information in real time translates to a more effective way to conduct business operations.

For example, AISense released Otter, the technology that can record audio and then convert the speech into text in real time using voice recognition algorithms. AISense also powers transcription for the Zoom Video Communications platform. Business operations can become more productive and data-driven by reducing the need to go back and manually record notes and then send them out to colleagues to get everyone up to speed.

AI can help business operations become more productive and data-driven by reducing the administrative burden of day-to-day tasks. This frees up your employees to focus on the thoughtful and impactful work that staying competitive in today’s digital age requires. The human aspect in the workforce will not go anywhere any time soon, but rather it will evolve. From business results to customer experience, AI provides us with the opportunity to automate these processes more fluidly and effectively.

AI-Enabled Communication Platforms

Through workforce communication platforms, organizations can deploy AI to better assist employees through a single user experience with an intuitive, on demand and automated communication experience to drive operational efficiencies across their entire workforce. 

Two of Phobio’s partners, Kronos and MarketSource, both use Rodio, our AI-enabled workforce communication platform. Employees are provided with a centralized workforce communication and collaboration system to deliver timely messages to front-line employees.

Other AI-enabled communication platforms like Drift are utilized to help organizations communicate with customers through live chat and automated marketing campaigns. Avaya’s Ava is another example of AI that can engage with customers using social media, chat and messaging channels to provide self-service support but is also able to deliver a customer to agent-based customer care.

Enabling users to get answers to questions in milliseconds provides new ways to engage employees and customers. Machine learning bots enable organizations to put their employees in the best situation to make decisions, be more productive and deliver impactful customer experiences by providing an intuitive interface, quick responses, and access to real-time information.

With millennials being the majority in the workforce, the adoption of AI is welcomed, and the outcome is a more informed, engaged and connected organization.

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