PRESS RELEASE: The Burnie Group hosts #EDGETalks: Artificial Intelligence in Operations: Where Can AI Fit in My Organization?

TORONTO, October 30, 2018 — The Burnie Group is pleased to announce #EDGETalks: Artificial Intelligence in Operations: Where Can AI Fit in My Organization? Featuring a keynote address by Mike Rhodin, former SVP at IBM and founder of IBM’s Watson Group. Mr. Rhodin’s 33-year career at IBM was infused with a passion for helping clients extract value from technology, improving business performance, and simplifying the way people work. Mr. Rhodin’s keynote will provide insight on the ways that artificial intelligence and automation are reshaping operations, augmenting human capacity, and changing the future of work.

“AI has been called the fourth industrial revolution. It is hard to conceptualize just how incredibly transformative its potential is,” says Doug Heintzman, Head of Innovation at The Burnie Group.

#EDGETalks: Artificial Intelligence in Operations: Where Can AI Fit in My Organization? will take place on the evening of Wednesday, November 7, 2018, at The National Club. Following the keynote address, we will have a fireside chat featuring Kathryn Hume, Frank Tsiribis, and Mike Rhodin.

Kathryn Hume – Vice-President, Product and Strategy at
Frank Tsiribis – Head of Insight Strategies and Risk Management, Enterprise Infrastructure, Initiatives, and Innovation (EI3) at BMO Financial Group.

Increasingly, companies are investigating the potential implications of AI on their enterprise, and if and how they should adopt it. This event will help separate hype from reality and fact from fiction. It will identify some key areas where AI is changing the way business is done.

For tickets visit:


About The Burnie Group

The Burnie Group is a Canadian-based management consulting firm that helps clients improve their businesses through the application of innovative strategy, rigorous analysis, world-class technology, and the continuous pursuit of operations excellence.  The Burnie Group specializes in Strategy, Operations, Robotic Process Automation (RPA), Artificial Intelligence (AI), Blockchain, and Workforce Management (WFM). Our programs deliver measurable, transparent, and guaranteed results.

Media Contact:
Bruna Sofia Simoes
Senior Marketing Manager

PRESS RELEASE: The Burnie Group achieves second consecutive top 100 rank in 2018 Growth 500 ranking of Canada’s Fastest-Growing Companies

–Canadian Business unveils its 30th annual list of Canada’s Fastest-Growing Companies – 

PRESS RELEASE: The Burnie Group achieves second consecutive top 100 rank in 2018 Growth 500 ranking of Canada’s Fastest-Growing Companies  TORONTO, ONTARIO– (Sept. 13, 2018) – The Burnie Group is pleased to announce that it has ranked No. 82 in the Growth 500 ranking of Canada’s Fastest-Growing Companies. This is the 2nd year that The Burnie Group has ranked in the top 100, with five-year revenue growth of 1,030%. The Toronto-based management consulting firm ranked No. 2 in the category of Canada’s fastest-growing professional services companies for 2018.

“The companies on the 2018 Growth 500 are truly remarkable. Demonstrating foresight, innovation and smart management, their stories serve as a primer for how to build a successful entrepreneurial business today,” says Deborah Aarts, Growth 500 program manager. “As we celebrate 30 years of the Canada’s Fastest-Growing Companies program, it’s encouraging to see that entrepreneurship is healthier than ever in this country.”

“Ranking in the Growth 500 two years in a row is a great honour, and we’re delighted to find ourselves amongst Canada’s best and brightest companies,” says David Burnie, Principal and Founder of The Burnie Group. “I believe this second nod confirms that we’re on the right track with our approach to client service and innovation. We want to thank our team and clients for making this possible once again.”

Ranking Canada’s Fastest-Growing Companies by five-year revenue growth, the Growth 500—formerly known as the PROFIT 500—profiles the country’s most successful entrepreneurial businesses. The Growth 500 is produced by Canadian Business. Winners are profiled in a special Growth 500 print issue of Canadian Business (packaged with the October issue of Maclean’s magazine) and online at and




About The Burnie Group

The Burnie Group is a Canadian-based management consulting firm that helps clients improve their businesses through the application of innovative strategy, rigorous analysis, world-class technology, and the continuous pursuit of operations excellence.  The Burnie Group specializes in Strategy, Operations, Robotic Process Automation (RPA), Artificial Intelligence (AI)Blockchain, and Workforce Management (WFM). Our programs deliver measurable, transparent, and guaranteed results.


About the Growth 500

For 30 years, the Growth 500 ranking of Canada’s Fastest-Growing Companies has been Canada’s most respected and influential ranking of entrepreneurial achievement. Developed by PROFIT and now published in a special Growth 500 print issue of Canadian Business (packaged with the October issue of Maclean’s magazine) and online at and, the Growth 500 ranks Canadian companies on five-year revenue growth. For more information on the ranking, visit 


About Canadian Business

Founded in 1928, Canadian Business is the longest-serving and most-trusted business publication in the country. It is the country’s premier media brand for executives and senior

business leaders. It fuels the success of Canada’s business elite with a focus on the things that matter most: leadership, innovation, business strategy and management tactics. Learn more at


Media Contact:

Bruna Sofia Simoes

Marketing & Sales Manager




INFOGRAPHIC: Demystifying Machine Learning

Machine Learning is the science of finding patterns in data and using those patterns to make predictions. It is the process by which, over time, machines (computers) are enabled without explicit programming, to learn, grow, and change autonomously through real-world interactions.  It is a subsect of Artificial Intelligence (AI).

AI refers to a computer system’s ability to perform tasks that normally require human intelligence, such as visual perception, speech recognition, communication, decision-making, planning, learning, and the ability to move and manipulate objects.

The infographic below explores the different applications of Machine Learning in a variety of industries, to learn more about AI and Machine Learning opportunities in your industry, please contact us for a free no-obligation discussion. We look forward to hearing from you.


INFOGRAPHIC: Demystifying Machine Learning

INFOGRAPHIC: Demystifying Machine Learning

PRESS RELEASE: The Burnie Group hosts #EDGETalks: Actively Engaged – Leadership and Innovation in Building Employee Engagement

TORONTO, May 28, 2018 — The Burnie Group is pleased to announce #EDGETalks: Actively Engaged – Leadership and Innovation in Building Employee Engagement. Featuring a keynote address by Norman Bacal, who, in his best-selling novel, Breakdown: The Inside Story of the Rise and Fall of Heenan Blaikie, recounts the cautionary tale of the perils of ignoring a firm’s culture and vision, and the danger of hiring as CEOs individuals with little to no management experience.

This event provides an opportunity for our clients and colleagues to discuss the very significant implications of employee engagement on organizational culture. As many of our clients are finding themselves in a rapidly commoditizing marketplace, organizational culture—and especially, employee engagement—remains one of the few competitive advantages you can leverage as a senior leader to grow and out manoeuvre your competitors.” says Darshan Jain, Head of Technology and Operations at The Burnie Group.

#EDGETalks: Actively Engaged – Leadership and Innovation in Building Employee Engagement will take place on the evening of Monday June 4th 2018 in the Gallery at First Canadian Place. Norm Bacal’s keynote address will be followed by a panel discussion led by industry thought leaders, academics and practitioners, including:

Richard Anton – Senior Vice-President, Chief Operations Officer, CIBC Mellon
Cathie Brow – Senior Vice-President, Human Resources & Communications, Revera
Nathalie Clark – Vice-President, HR TD Securities & Risk Management, TD Bank Group
Rob Lokinger – Chief Operating Officer, AppCentrica

With extensive research showing that organizations face a radically shifting context in the workplace, an engaged workforce should be a top priority for senior management.  Converging issues such as flatter hierarchies leaving less 1:1 time with direct managers, accelerated career development expectations, and a technology-driven 24/7 work environment are driving the need to rewrite the rules of employee engagement.  With so much on the line, what does it take for an organization to really understand its culture and create an inclusive and engaging corporate environment?

For tickets visit:

About The Burnie Group
The Burnie Group is a highly specialized operations consulting firm that helps clients improve their businesses through the application of innovative strategy, rigorous analysis, world-class technology, and top-tier domain expertise.  The Burnie Group specializes in StrategyOperationsRobotic Process Automation (RPA)Blockchain, and Workforce Management (WFM).

Media Contact:
Bruna Sofia Simoes
Marketing Manager


Source: The Burnie Group


PRESS RELEASE: The Burnie Group receives Blue Prism Silver Partner Award in Robotic Process Automation

PRESS RELEASE: The Burnie Group receives Blue Prism Silver Partner Award in Robotic Process Automation  TORONTO, ONTARIO– (June 1, 2018) – This latest achievement builds upon an already deep and long-standing relationship with Blue Prism. One of North America’s first Blue Prism partners, The Burnie Group helps clients transform their operations through the delivery of robotic process automation, augmented by thoughtful business process redesign and performance management. This approach provides substantial cost savings, streamlines and simplifies operations, and eliminates waste, errors and the risk of fraud.

“The Burnie Group is honoured to be recognized as a Blue Prism Silver Partner,” said David Burnie, Principal and Founder of The Burnie Group. “We constantly strive to be at the forefront of what’s new, and what stands to have incredible influence. We were the first consulting firm in Canada to adopt and embrace Robotic Process Automation (RPA), and we’ve been very successful in building this practice, this award is a testament to that.”

Recently, The Burnie Group supported ATB Financial in achieving Blue Prism’s 2018 ROM Excellence Award. An accolade presented to the company who has been judged to have achieved the best performance through implementing the Robotic Operating Model that leverages object reusability, appropriate controls and organizational design to maximize business benefits and scalability.

With the demand for RPA and The Burnie Group’s services continuing to increase, together The Burnie Group and Blue Prism are helping clients deploy digital workforces across North America.




About The Burnie Group

The Burnie Group is a Canadian-based management consulting firm that helps clients improve their businesses through the application of innovative strategy, rigorous analysis, world-class technology, and the continuous pursuit of operations excellence.  The Burnie Group specializes in Strategy, Operations, Robotic Process Automation (RPA), Blockchain, and Workforce Management (WFM). Our programs deliver measurable, transparent, and guaranteed results.



Media Contact:

Bruna Sofia Simoes

Marketing & Sales Manager




INFOGRAPHIC: The Automation Race: Comparing 5 RPA providers

Robotic process automation (RPA) is a disruptive technology that can improve workforce productivity, accelerate process execution, reduce process error rates, and improve customer satisfaction. Companies that are quick to recognize the potential of automation stand to have considerable cost advantages and organizational agility. However, it can be difficult to know which provider has the automation solution specific to your company’s needs.

In this infographic, we compare the features and strengths of 5 leading RPA providers.

INFOGRAPHIC: The Automation Race: Comparing 5 RPA providers

INFOGRAPHIC: The Automation Race: Comparing 5 RPA providers


Digital Disruption and Private Equity: Understanding Effects and Opportunities.

Disruption is an age-old force of change that both drives and destroys. Forces such as globalization and the increasing pace of innovation diffusion are accelerating the frequency of disruption and the impact it can have on industry. As a result, value can be both created and destroyed seemingly overnight. By their nature, private equity (PE) firms have always had to be quick to respond to disruptive trends.

Digital Disruption and Private Equity: Understanding Effects and Opportunities.  With the rise of digital technologies, the pace of disruption and the speed of its diffusion has increased dramatically. If PE firms are to survive and thrive in this new era, they must consider the effect of digital disruption on their portfolios as well as their internal operations. They must also continuously adjust their strategy and decision-making framework, with consideration to how disruption affects industries, portfolios, and internal firm operations.


How does disruption alter industries?


With new disruptive innovations come new markets and value networks. These innovations can fuel new business models (e.g. ride-sharing applications helping to launch the sharing economy) and can disrupt existing markets and networks (e.g. how ride-sharing changed the taxi industry).

Furthermore, the very nature of what a business is changing. The power of “open innovation” means that the advantages of the classical firm as the most efficient means of creating value are giving way to ecosystems that have a much larger and more efficient means of assembling and reconfiguring resources in the pursuit of value creation.


2. Customers.

Digital disruption has irrevocably changed the customer journey. Customers of the “digital native” generation now expect information about a product to be accessible from the palms of their hands. They expect to be able to compare prices, see demonstrations, and receive feedback and recommendations from their social networks about products. Companies that can meet these new digital expectations can reap the value, while those that do not will rapidly succumb to irrelevance and insolvency.


3. Products.

As pressure mounts to meet increasingly demanding customer expectations of “the newest thing,” product lifespans get shorter. Long established products can quickly become obsolete. The advent of the smartphone leading to the decrease in relevance of Nokia, Blackberry and Motorola is a clear example. The fate of Kodak, once one of the most powerful brands in the world, serves as a stark reminder of what can happen when digital disruption is ignored. This example is especially poignant as it was Kodak itself that invented the digital camera and the digital SLR camera. In Kodak’s case, the curse of a powerful product-linked brand, an aversion to self-disruption, and the inability to recognize customers’ latent desire to share photos with friends and family in real time, led Kodak to fall from the Fortune 500 to bankruptcy in less than 15 years.


How does disruption create new value opportunities for PE?

As industries are disrupted, PE firms must themselves ask the following:

  1. Is a portfolio or target company at risk for becoming devalued by new technology?
  2. Is a target company appropriately prepared to embrace new technology?
  3. Is there an opportunity to capitalize on value emerging elsewhere as a result of disruption?

The ability to recognize the potential value of digital technologies in yet-unconsidered applications can add limitless value to a PE portfolio. Consider, for example, the emergence of bitcoin as a disruptive new asset class in the financial industry. It turns out that bitcoin’s underlying technology, blockchain, will be far more disruptive than bitcoin and will fundamentally impact countless industries. The ability to recognize the potential value of digital technologies in yet-unconsidered applications can add significant value to a PE portfolio.

Another source of value generated by digital disruption and efficient diffusion is accelerated innovation. Rather than focusing on developing a new product that may soon be outdated, accelerated innovation focuses on using new technologies to re-engineer research and development processes. Approaches include reducing lead times by engineering product elements simultaneously, reducing the learning curve by quickly incorporating user feedback, and increasing problem-solving efficiency by restructuring the organization. Despite the associated risk of failure, the ability of accelerated innovation to cut costs and reduce production times has proved highly valuable to customers, and worth considering not only as a framework to evaluate assets in a PE portfolio but as a means of improving the efficiency and effectiveness of the PE firm itself.  


How can PE firms realize new value opportunities?

In the age of digital disruption, it is no longer sufficient for PE firms to evaluate a target company using traditional value indicators (e.g. cash flow, capital expenditures, and historical performance). Historically valued companies may still be vulnerable to the newest wave of digital disruption. Others that appear to be digital laggards may actually have the potential for huge value generation given the right injection of capital, technology, and coaching.

To realize a valuable investment, PE firms must conduct due digital diligence on potential investments, asking the following:

  1. What is the target company’s level of digital maturity? I.e. have multiple aspects of the company–talent acquisition, marketing, sales, and customer relations, etc.—been digitized?
  2. What is the target company’s strategy for managing digital disruption?
  3. Does the target company have a method for measuring the financial impact of digital disruption and a formal discipline of data-driven decision making?
  4. Are the target company’s operations being reshaped by any industry trends?
  5. What technology has the potential to destroy profit across the current value chain?
  6. Which companies might emerge as unexpected competitors?
  7. Does the company’s senior leadership team support a culture of innovation and risk-taking?

Digital disruption can increase the potential revenue of a business that is culturally prepared embrace disruption. As a result, it can generate new business growth in new and adjacent markets. To capitalize on this potential value, PE firms must calculate risks and opportunities by conducting conduct rigorous digital due diligence on potential investments.  They should also consider what value they can contribute to prospective and existing investments to help those companies survive and prosper in an age of accelerating innovation.


How can disruption impact PE firms internally?

The primary focus of most PE firms is on the operations and business prospects of their portfolio companies. The internal operations of the firm itself are often of secondary importance. But digital disruption is as much of a risk, and a potential opportunity, for firms. Disruption can impact investors and partners alike, altering expectations of business conduct and introducing new security threats.

PE firms should address their own place in their digital ecosystems by asking:

  1. How will new and growing threats to privacy and cybersecurity be addressed?
  2. Should the firm buy an existing system to enhance its digital capabilities, or build its own?
  3. Which disruptive technologies can be utilized to improve and enhance firm operations?


How can PE firms use disruptive technology to optimize internal operations?

Despite sophisticated financial tools, transactions currently rely on manual processes that are legally and paperwork-intensive. As a result, PE firms are an ideal environment for leveraging many disruptive technologies. The following technologies can all be implemented to optimize PE internal operations:

  • Robotic process automation (RPA): Improves productivity through automation. Processes that can be improved using RPA include investor reporting, waterfall calculations, capital call and distribution notices, performance calculations, tax compliance, management reporting, and regulatory reporting.
  • Advanced cybersecurity: Enables proactive protection and improves risk mitigation. Can be used to secure internal PE firm operations, including the exchange of money and sensitive information during deals and the management of the portfolio company post-deal. Cybersecurity ensures the safety of finances, intellectual property, and customer data.
  • Cloud: Improves the operational speed and ease of deployment, resource utilization, the agility of adjustments, security of materials, and containment of costs.
  • Advanced analytics: Drives decision making and insight with deep pattern recognition and outcome prediction. Use of analytics can also improve and accelerate the due diligence process. Advanced analytics also can rationalize unstructured and complex data sets already available.
  • Blockchain: Improves workflow efficiency, fraud reduction, and onboarding and identity management. Blockchain can also be used to secure deal execution.
  • Artificial Intelligence: Improves insight and exception handling. AI can be applied to valuations, using qualitative and quantitative variables to estimate the odds of achieving higher risk-adjusted returns. Natural language processing can improve sentiment analyses, identify trends, and automate call centres. A noteworthy example, Deep Knowledge Ventures uses an AI system, called VITAL, with its investment committees. This system makes decisions by scanning prospective companies’ intellectual property, clinical trials, financing, and previous funding rounds to determine the attractiveness of an investment and assess related risk. 


The final word.

To develop the operational framework necessary to manage internal and external disruption, organizations require a well-designed strategy led by an aligned and engaged management team. By combining a robust operating framework with a formalized approach to strategic innovation, organizations can foster a culture of continuous improvement and adjustment. This includes looking outside of the organization to forecast possible scenarios, new domains, and potential offerings. Internally, this includes the reallocation and definition of roles and responsibilities with leadership capabilities. With these strategies in place, the focus can shift to the creation of an innovative culture that seeks new value in both internal operations and external performance.


Digital Disruption and Private Equity: Understanding Effects and Opportunities.


The impact of employee engagement on organizational performance

The impact of employee engagement on organizational performance  There is a well-supported link between employee engagement and business performance. The logic is simple: a more engaged workforce leads to increased operational efficiency, happier customers, and higher profits.  But how does a more engaged workforce produce these desirable outcomes, and how can a business improve engagement?

One of the key differences between the performance of an engaged and a disengaged employee is “discretionary effort,” or “the level of effort people could give if they wanted to, but above and beyond the minimum required.”[i]  Simply put, if employees are involved in and enthusiastic about their work and workplace they are likely to exceed the expectations and requirements of their position. But how can businesses encourage higher levels of engagement in their staff? Moreover, how can they prevent disengagement from occurring in the first place?

Engaged employees are passionate about their work. They feel motivated by their leaders and are confident they can achieve success in their roles. Engaged employees see the purpose in what they do every day and play a significant role in business successes.

However, many workers do not experience this level of engagement. According to research conducted by Gallup, around 50% of the US workforce is disengaged, and 15% to 20% is actively disengaged.[ii] Disengagement may be caused by a poor relationship with a direct manager or by a lack of meaningful feedback or recognition. It may even be a basic misalignment between the company and employees’ values. Without a way to measure employee engagement, business leaders are left to guess at what actions will improve the employee experience.

Collecting and monitoring employee engagement metrics enhances business leaders’ ability to detect problems in their organization, take specific action to address issues and opportunities, and evaluate subsequent progress.

With our EnGauge employee engagement program, we at The Burnie Group help our clients understand how their businesses are performing across ten key engagement metrics:

  1. Happiness
  2. Wellness
  3. Satisfaction
  4. Personal growth
  5. Relationship with peers
  6. Feedback
  7. Recognition
  8. Relationship with manager
  9. Alignment
  10. Ambassadorship

The impact of employee engagement on organizational performance  Using this information, we work with leaders to develop action plans to improve employee engagement.  Through a repeatable improvement cycle, we help businesses take control of employee engagement and achieve the desired results: increased operational efficiency, happier customers, and higher profits.

Looking at the list of metrics above, how do you think your business compares? If you see room for improvement, give us a call and realize the potential of an engaged workforce.

The impact of employee engagement on organizational performance

 By: Bret McCaffrey, Senior Associate

[i] Earning Above and Beyond Performance: Understanding the effective use of positive reinforcement (ADI Aubrey Daniels International)

[ii] State of the American Workplace (Gallup News), 2017

INFOGRAPHIC: 22 Benefits of RPA

This infographic is a window into the world of Robotic Process Automation. If you are interested in exploring RPA opportunities in your industry or want to know more about implementing RPA in your organization, please contact us for a free no-obligation discussion. We look forward to hearing from you.

INFOGRAPHIC: 22 Benefits of RPA

INFOGRAPHIC: 22 Benefits of RPA

29 Cutting Edge Applications of Artificial Intelligence

29 Cutting Edge Applications of Artificial Intelligence  Artificial Intelligence (AI) is the theory and development of computer systems that can perform tasks that normally require human intelligence. These tasks include visual perception, speech recognition, decision making, and language translation. Systems capable of performing such tasks are steadily transitioning from research laboratories into industry usage.

AI technology is unique in that it is flexible in application. It can be used to improve processes, enhance interactions, and solve problems that, until recently, could only be performed by humans. AI’s advanced abilities include natural language processing (NLP), machine learning, machine perception, and enhanced analytics.

The list below details 29 cutting-edge applications made possible by AI technology.



Natural language processing (NLP) is a sub-category of AI that attempts to bridge the gap between human and computer communication. AI-enabled systems such as IBM’s Watson use NLP to understand and respond to the nuances of human language. This allows for more accurate analysis of data sets and communication of insights.

  1. Customer interaction chatbots — Chatbots are computer programs that are commonly used to interact with customers by audio or text. Conversica, for example, is a virtual sales assistant that communicates persistently and politely with prospective sales leads. Conversica uses email to engage, qualify, and follow-up with leads, allowing the sales team to focus their efforts on closing deals.
  2. Financial chatbots — In the financial industry, chatbots such as aLVin are used to interact with brokers. They can answer questions, understand intent, and direct brokers to their desired products and information.
  3. Virtual assistants — Beyond chatbots, AI can power more complicated virtual assistants that can recognize client needs and complete various tasks. Expensify‘s virtual assistant, Concierge, assists in the automation of expense reports and travel arrangements for companies. It can inform clients of real-time price changes and can even file receipts on their behalf.
  4. Communication systems – AI-powered communication systems can also be used to manage relations between peers and stakeholders. CrystalKnows, a personality detection software, uses NLP to evaluate LinkedIn accounts and develop a profile of how to most effectively speak to, work with, or sell to an individual. Crystal can even draft emails to anyone based on the preferred tone suggested by his or her online presence.
  5. Legal assistants — The language processing capabilities of AI assistants can be tailored to a specific industry. LegalRobot’s AI assistants are designed to review legal documents and make suggestions for language clarity and strength.
  6. Cognitive retail – Virtual assistant capabilities can be integrated with other customer relationship management products to provide in-person levels of service via online platforms. The North Face‘s personal web-shopper, XPS, uses NLP to understand customer need as would a human representative. It then uses machine learning to make informed product recommendations based on customer history, location, and other data.
  7. Personal assistants – AI can also be used on a personal device to simplify daily tasks. Gluru technology, for example, is used to power a task management application that uses NLP to analyze a user’s conversational data, such as their email. This app can identify tasks, generate a personalized to-do list, and even provide actionable buttons to complete each task.
  8. Web speech – New language-based technological advancements in AI can improve the web navigation and searching experience. These web speech APIs integrate voice recognition technology, syntactical analysis, and machine learning to seamlessly convert voice to text and vice versa. This click- and typing-free internet interaction can improve information accessibility for those with a disability or low technological acumen.



Machine learning is an application of AI that allows systems to process data and learn to improve the performance of a specific task without explicit programming.  Deep learning is a form of machine learning that mimics human learning patterns to gain an understanding of unstructured data sets and generate intelligent decisions.

  1. Medical decision making — Deep-learning programs such as Enlitic can optimize physician decision making by analyzing a patient’s past medical history, diagnostic information, and symptoms to provide actionable insights. These programs learn as they process data, improving their ability to identify diseases and provide treatment planning.
  2. Healthcare analytics — Deep learning can also be used to compile, analyze, and interpret collaborative data. Flatiron, for instance, has developed a cloud-based platform for healthcare professionals that compiles insights, empirical data, and patient experiences to improve oncological care on a real-time basis.
  3. Bioinformatics – In the field of bioinformatics, scientists use AI-software to identify patterns in large data sets, such as sequenced genomes and proteomes. This analysis can help in the development of new drugs to tackle diseases by determining which proteins are encoded by a certain gene. Atomnet is a deep-learning technology that analyzes the structure of proteins known to cause disease and designs drugs accordingly.
  4. Emotional detection —Emotional detection systems powered by AI can detect human emotions without visual input. Researchers at MIT have developed EQ Radio, a system that learns to identify human emotions based on heartbeat data collected by wireless signals. This technology may one day be used by smart homes to detect if a resident is experiencing a heart attack.
  5. Fraud detection — Fraud prevention has always been a major challenge for the financial industry. PayPal and other eCommerce companies have started to use deep-learning fraud-detection algorithms to monitor customers’ digital transactions and identify suspicious behaviours. A study by LexisNexis found that this deep-learning approach to security has reduced PayPal’s fraud rate to 0.32% of revenue, a 1% improvement over the industry average.
  6. Cyber Security — AI-enabled cybersecurity programs analyze and organize internal network data to identify potential threats. The security program RecordedFuture uses machine learning and NLP to contextualize information and provide actionable analyses.
  7. Procurement optimization – Companies can use AI internally to enhance business operations such as procurement. Tamr, a data unification software, uses machine learning to clean, analyze, and sort procurement data. It identifies savings opportunities, bundles spending across business units, and exposes supplier risk.
  8. Customer interactions — While NLP allows virtual assistants to interact easily with customers, deep learning allows them to locate and provide the desired information. The AI model DigitalGenius analyzes historical customer service transcripts in order to recognize successful customer interactions. This allows the model to predict meta-data for new cases and provide suggestions for automated customer responses.
  9. Optimized gaming — The gaming industry, previously focused on the level distinctions of “easy,” “medium,” or “hard,” is now using AI technology to develop self-optimizing and -evaluating games.  These new AI-powered games keep players engaged by continuously adjusting difficulty and strategy to suit player ability.
  10. Military planning — In a military setting, AI can be used to increase deployment efficiency. Autonomous machines (including drones and satellites) share data in real time to develop actionable strategies. The U.S. military AI system JADE evaluates historical data, combines information with learned reasoning, and presents suggestions to execute large-scale plans in minimal time.



Machine perception is the ability of a system to simulate human perception of the world. AI uses machine perception to extract information from different data sources. Computer vision is a type machine perception that allows AI to extract information from images.

  1. Medical imaging — Computer vision represents a huge technological advancement for medical imaging and preventative care. The diagnostic program Zebra Medical Vision collects and analyzes medical scans for various clinical identifiers. It then accesses a database of millions of scans, enabling it to provide critical information such as the location of a tumour or a patient’s risk of cardiovascular disease.
  2. Manufacturing — The manufacturing sector is increasingly turning to robotics to speed up repetitive tasks. AI-enabled robots use computer vision to complete tasks and to adapt to changing environmental conditions, broadening the types of tasks available to robots and preventing costly mistakes on the assembly line. Fanuc‘s Gakushu robots use computer vision and a machine learning software to collect and evaluate data for path, speed, and task optimization in aerospace manufacturing.
  3. Service industry – Some AI-enabled robots can not only understand human language but can recognize human emotions. Using computer vision, Softbank‘s humanoid robot Pepper can interpret facial expressions as human emotions and generate responses accordingly. Pepper can also recognize and remember individual faces and preferences. It is primarily used as a greeter in Japanese office buildings, restaurants, banks, and stores.
  4. Financial industry — In the financial industry, AI programs can learn to identify potential high-yield customers, to recognize fraud, and even to forecast changes in stock trends.  To further reduce fraud, the financial application Face++ uses computer vision for facial recognition to secure users’ financial transactions.
  5. Autonomous delivery – Companies are increasingly using AI for commercial navigation purposes. Autonomous delivery systems, such as Amazon‘s delivery drones and Domino‘s Robotic Unit, use computer vision to efficiently navigate obstacles and optimize routes. Beyond commercial delivery, Matternet’s autonomous drone network in Switzerland aims to reduce medical testing times by flying diagnostic materials between hospitals and labs.
  6. Transit safety — AI technology is paving the way for autonomous cars and accident-free transit systems. The combination of deep learning and computer vision allows cars to observe and safely interact with the surrounding environment. Road safety can be further increased by AI-enabled navigation systems, which alert drivers to potential accidents and suggest alternative navigation routes.
  7. Geospatial analytics — Geospatial analytics use computer vision to gather and compare satellite imagery with historical data in order to develop insights. Using these insights, AI-enabled satellites can track economic trends from space. Orbital Insight, for example, predicts retail sales based on satellite images of retail store parking lots.
  8. Childcare — AI devices use computer vision to recognize faces and navigate around obstacles, but a new Google patent suggests they can even be used to provide childcare.  Google’s AI babysitter system learns to recognize different features of a home and to differentiate between family members. The system can recognize when a child has been left alone for too long, or has wandered dangerously close to a socket, and alerts the parents accordingly.



Predictive analytics are used by programs to analyze historical data in order to predict future outcomes. When combined with AI platforms, analytic ability increases in speed, scale, and application.

    1. Marketing — Some predictive models can be used to analyze consumer data and inform marketing decisions. Magnetic, for instance, can predict the most effective advertisement to present a particular consumer and can choose to present the selected advertisement to the consumer without human supervision.
    2. Data extraction — Data-extraction programs use AI to analyze and extract specific information from documents. Xtracta, for example, allows various retail applications to extract data from receipts. This information, combined with predictive analytics, generates useful statistical reports and relevant buying suggestions for the application user.
    3. Social Network Analytics — Social networks can provide valuable marketing data, but also produce linguistically complicated datasets. In order to produce usable information, user profiles must be semantically analyzed using NLP. Companies can then use predictive algorithms to identify a customer’s preferences and web navigation patterns in order to provide targeted web advertising.

Development of AI technologies is actively being encouraged through projects like Soar—a cognitive architecture project aimed at developing computational building blocks for intelligent agents—and OpenCog—an open-source software project intended to create a framework for artificial general intelligence. Through such collaboration, AI capabilities continue to advance, thus expanding application potential.

29 Cutting Edge Applications of Artificial Intelligence

 By: Jenya Doudareva, Associate & Lokesh Patil, Associate