Article | July 26, 2020
Are self-driving cars safe? As the automotive industry moves towards higher levels of automation, it’s important for the answer to this question to always be yes. At TomTom, it’s our vision to create a safe, connected and autonomous world – and a big role in making autonomous driving safer is played by ADAS and HD maps. Maps – ADAS and HD – are one of the four pillars of autonomous driving. Together with onboard sensors, driving policy and actuators, they form the technology that enables automated and autonomous driving. HD maps specifically improve localization to centimeter-level accuracy and sensor perception, which leads to safer path planning by automated driving systems.
Article | June 23, 2021
Customers feel connected when they have a one to one conversation with the seller. It makes the product/service look promising and convincing to them. But it is impossible to provide one on one interaction to every buyer. It requires a bounty of staff and resources. And God forbid if the product/service does not succeed, all efforts go down the drain. Thus, there should be a permanent solution to provide personalization to the buyer, which takes minimum costs.
This solution is named Conversational AI. This is a budding conversational sales and marketing strategy that is of immense potential. A simple example is Chatbots. Chatbots are responsible for a lot of success in various departments of an organization. From solving queries to lead generation, Chatbots have proved their efficiency to the fullest.
But chatbots are just a part of conversational AI. This extensive system can change the outlook of any industry when implemented in the right way.
Talking to machines is getting more comforting and convenient. Research indicates that conversational AI is going to impact businesses in a significant way.
Stats of transformation in business departments due to AI in the next five years
• 61% personalization of content
• 60% prediction of buyer’s journeys
• 59% marketing productivity
• 59% digital management
The above stats indicate that AI will impact content, digital marketing, sales, and many other departments. Conversational AI will assist in boosting the sales graph to rise in each department.
Advantages of implementing conversational AI in Business
Attractive Customer Experience (CX)
All businesses want their customers to have an amazing experience while dealing with them. And conversational AI takes it to the next level. It is designed in a way that provides the best conversation experience with the customer. Gone are the days when machine conversations seemed robotic. The new AI infrastructure promises a personal and intimidating conversation, along with multilingual options.
The data collected by the organization should be funneled in the right way to provide a great experience to every user. If the data is used correctly and implemented in the AI, the CX of your organization is sure to set examples.
Intelliticks is one of the examples of emerging conversational AI platforms to provide the best CX. It has Facebook messenger integration to connect with the users. This platform saves time and money while delivering engaging answers to the customers round the clock.
Provides an Omnichannel Approach
Customers need different channels while interacting with a particular brand. Some prefer emails, while some prefer calls. As there cannot be one channel of communication and management of all channels requires an intelligent effort, integrate conversational AI to make things fall in place for you.
Conversational AI unifies the data and gives a clearer understanding of customer’s data. The algorithm is designed to provide your organization with the best way of connecting with the customers through their preferred channels.
Assistance in promoting your content
Promotion of content is still a tedious task for many organizations. Posting blogs, articles, social media posts are easier but assuring that it reaches the right audience is still a way through a dense forest. While SEO and search engines work well, conversational AI bots can prove a breakthrough for content promotion.
For example, when the chatbot answers a specific query, it can provide the user with a link to the related article or blog. Thus, the user gets all the required information and more through the chatbot. On the other hand, your content is promoted to the right audience. Once the chatbot recognizes the regular pattern of the customer, it can promote the related content through the right channel.
Reduce Administrative Burden
With the implementation of conversational AI, the reduction of workload and use of resources is unimaginable. The administration can carry out their designated jobs with full assistance from CAI at every stage. These advanced chatbots can handle and immaculately organize the work of the various departments in the organization.
From intimating about the meeting to the concerned individuals to organizing fun activities, every little thing can be managed by conversational tools. An organization does not have to ask for an employee’s schedule individually. The employee can tell the software their schedule, and the conversational AI merges the information of all the employees and coordinates accordingly.
When introduced in the HRIS system, the HR department will have the best assistance to implement and ease their tasks. People have to speak to the software, and their schedules will be synchronized in the system.
Things to consider before introducing Conversational AI in the system
Merging of channels
When a user chats with a chatbot and the chat needs to be taken forward by the concerned human agent, he should have the history of the conversation. The entire data about the customer with its history and complaints should be accessible to the agent. This implies that all the channels such as voice, chat, mail, and web should be integrated seamlessly in the CAI channel.
Explore areas wherein CAI can be deployed
CAI is not just customer-centric. It can help all the departments of the organization in its own way. Like the former example of the HRIS, CAI can be implemented in other departments, too. It can assist in designing, determining product life cycle, data analysis, employee training, and much more. So do not keep CAI defined to enhance customers, employees, or sales department. Explore the opportunities for conversational AI and introduce it wherever possible.
Make the CAI highly engaging
Everyone knows when they are talking to a chatbot, but that does not mean the conversations have to be ordinary. Hiring creative writers and having them design intriguing statements for discussions makes the CX enriching.
For example, Hyundai CAI asks the customers several questions before telling them about the inquired product. Like “Before we talk about your favorite car, let’s chat about you so that I can be more helpful. Would you say you are more into...?” Then it provides three options like city life, outdoors, unique experiences, etc. Thus based on these answers, a marketing funnel is generated, and the correct type of car or cars is recommended to the customer.
Thus, engaging conversations can prove highly successful in generating and converting leads via CAI.
Conclusion: CAI- The best solution for business
The possibilities created by CAI for businesses are endless. You should identify the right way to introduce and implement it in your business. This means you have to identify which conversational tools suit your business in the best way. It would be best to educate yourself about the features, integrations, and their work in your organization.
The integration of CAI enhances the buyer’s journey and helps businesses meet their customers' demands easily. This, in turn, increases customer retention. You need to push boundaries and challenge yourself to stay ahead in the digital race. If CAI seems expensive or complicated, just begin with a basic chatbot to answer general questions and welcome your customers when they visit your site. Once you take this step forward, you will notice how important it is to stay up to date and include CAI in your organizational processes.
Conversational AI is not magic, but it is the best combination of AI and ML!
Frequently Asked Questions
What is conversational AI used for?
Conversational AI is used to enhance customer experience and provide them with a personalized approach. It means that the machine has a human-like conversation with the human. Organizations or individuals can use conversational AI to communicate seamlessly with devices.
What is the difference between chatbots and conversational AI?
Chatbots are used to build only text assistants, while conversational AI is used for text and voice assistants. Conversational AI is more intelligent, smarter, and understands the human language precisely.
What are conversational AI tools?
Conversational AI tools imply chatbots, messaging apps, and voice assistants. These can be implemented in businesses to provide a seamless customer experience. Software that integrates all or some of the above and eases business processes is an example of CAI.
"name": "What is conversational AI used for?",
"text": "Conversational AI is used to enhance customer experience and provide them with a personalized approach. It means that the machine has a human-like conversation with the human. Organizations or individuals can use conversational AI to communicate seamlessly with devices."
"name": "What is the difference between chatbots and conversational AI?",
"text": "Chatbots are used to build only text assistants, while conversational AI is used for text and voice assistants. Conversational AI is more intelligent, smarter, and understands the human language precisely."
"name": "What are conversational AI tools?",
"text": "Conversational AI tools imply chatbots, messaging apps, and voice assistants. These can be implemented in businesses to provide a seamless customer experience. Software that integrates all or some of the above and eases business processes is an example of CAI."
Article | April 12, 2021
Digital Transformation is not a magic wand; it is a complex yet essential enterprise commitment to change. Companies that have succeeded have reaped significant benefits. The Deloitte Digital Transformation Survey 2020 found that greater digital maturity is associated with better financial performance. The higher-maturity companies in this year’s sample were about 3X more likely than lower-maturity companies to report annual net revenue growth and net profit margins — a pattern that was consistent across industries.
Unfortunately, most enterprises do not fully appreciate what it entails. Some see it as a technology or a budget problem; others believe it is an optional strategy — they are both wrong. To truly succeed, transformation needs to be led from the top by setting the strategy and allocating resources. Antonio Neri of HPE hits the spot when he says, “Digital transformation is no longer an option for enterprises, but a strategic imperative.”
For me, one of the most significant examples of top-driven organisational change is Jeff Bezos’ call to “Rearchitecting the Firm” in 2002. It is a seminal work. The principles of this mandate went on to form the backbone of Amazon in the modern cloud world. It was clear, direct, and backed up by management action.
More than 75% of CEOs agreed that the pandemic sped up their companies’ transformation plans
COVID is a catalyst for change
The flurry of digital technology solutions spurred by COVID-19 presents a unique opportunity for enterprises to rethink how technology decisions are made and apply them in new and meaningful ways. Covid-19 dramatically accelerated technology adoption across all industries. According to a Fortune-Deloitte CEO survey and the KPMG 2020 CEO Outlook Survey, more than 75% of CEOs agreed that the pandemic sped up their companies’ transformation plans. As Microsoft CEO Satya Nadella noted, “We’ve seen two years’ worth of digital transformation in two months.”
80% of companies plan to accelerate their companies’ digital transformation plans, primarily incentivized by the global pandemic implications. The same study also concludes that only 30% of digital transformations have achieved their objectives which is troubling.
80% of companies plan to accelerate their companies’ digital transformation plans, however only 30% of digital transformations have achieved their objectives - BCG Research
Most people forget that digital transformation is less about technology and much more about the organization’s culture and business shift. Key stakeholders need to rethink customer experience, business models, and operations fundamentally. It is all about finding new ways to deliver value, generate revenue, improve efficiency, and, most importantly driving sustainable innovation. Bear in mind, just moving to the cloud is not Digital Transformation.
Crises Breed Innovation
I am of the firm belief that uncertainty drives creativity. Crises are the breeding ground for innovation. You must make decisions quickly, and you never have enough time or information to weigh difficult choices thoroughly.
McKinsey’s analysis shows that bold innovators emerge from crises substantially ahead of peers — and maintain this advantage for years to come. Innovators not only outperformed the market during the financial crisis but continued to widen the gap during and after the recovery. Analysis of the performance of approximately 2,000 companies between 2007 and 2017 against the S&P 500 reinforces those conclusions: staying focused on growth and innovation through a downturn helped the top-performing companies to generate higher returns to shareholders.
Staying focused on growth and innovation through a downturn helped the top-performing companies to generate higher returns to shareholders
Antonio Neri and other leaders confirm that as the pace of technology disruption continues to accelerate, digital-native and digitally transformed companies are outpacing their competitors.
The McKinsey study shows that roughly one in ten companies in their sample achieved higher revenue growth, innovation, digital adoption, and profitability than the others over the entire 2007–17 economic cycle and during the downturn years. The outperformers also delivered excess returns of roughly 8%, while the rest hovered around zero throughout the period.
So, what does it take to succeed?
Do existing leadership teams have the skills to undertake true digital transformation? I thought it would be a good idea to look at how companies are hiring critical resources. A study by professors from Harvard and Darden and executives from Spencer Stuart published in the Harvard Business Review addressed this specific question. The team looked at more than 100 search criteria for C-suite positions in Fortune 1000 companies across a broad range of industries, and the results were very suggestive.
There has been a rise in tech and digital expertise search even before the pandemic: 59% of executive searches included technological or digital knowledge. Company boards were asking for these skills across a wide variety of roles. This fact also suggests that people with the right skill sets are already in leadership positions. Not surprisingly, 100% of the specs for CIOs, CMOs, and CTOs sought technical or digital skills. However, the functions that got neglected in the search for technological and digital expertise were more revealing. Less than a third of the job specs for CHROs and chief accounting officers mentioned these required skills. Even more worrying — only 40–60% of searches for roles such as CEO, board director, and CFOs required digital know-how.
At the very minimum, we need all leaders to understand how to build digital businesses. This shift alone could be the difference between success and failure.
But is that enough for now?
Almost every organization has stepped up its digital transformation efforts in 2020–21. Success is as much about the right technology platform choice as it is about leadership, agility, talent, and a clear vision. A new and emerging factor is consumers wanting the brands they use to focus on sustainability issues. So do employees and prospective employees. The driver for this shift largely springs from realizing that human activities’ ecological footprint is a probable cause for the crisis we face today.
While we keep talking about the usual polluters like utilities, transportation, agriculture, and climate change causes, some lesser-discussed and more exciting facts would make the issue more relatable.
Did you know that in processing 3.5 billion searches a day, Google accounts for about 40% of the internet’s carbon footprint? They have been carbon neutral since 2007, but their infrastructure still emits a considerable volume of CO2.
Did you know that Bitcoin currently uses enough power (121 terawatt-hours) to run Cambridge University for almost 700 years?
To address sustainability in a meaningful manner, we need to take a holistic view of the players, their impact and then push for a mutually beneficial solution . Else, it is bound to fail.
As a first step, 26 CEOs of Europe-based companies have signed a Declaration to support Green and Digital Transformation of the EU. They formed a European Green Digital Coalition, committing on behalf of their companies to not only make the tech sector to become more sustainable, circular, and a zero polluter but also to support sustainability goals of other priority sectors such as energy, transport, agriculture, and construction while contributing to an innovative, inclusive and resilient society.
Like these CEOs, Accenture also believes that there is great value at the intersection of digital technologies and sustainability — they call it Twin Transformers. Companies leveraging both are 2.5X more likely to be among tomorrow’s strongest-performing businesses than others.
BigTech is conscious of its responsibilities to the climate. Almost all majors players have made pledges to reverse CO2 emission. Since they are all profit-driven, I am sure they have also figured out this also means good business by the numbers too (a counter-intuitive rationalisation but better than getting caught in the justification game)
In the future, a company’s commitment to ESG-related programs will drive the ability to attract investors and retain talent. Companies also realize that ESG factors, when integrated into strategic digital transformation decisions, may offer potential long-term performance advantages. One of the critical levers for moving to sustainable systems will be technology, a lot of technology, and a lot of investment. But how do we make it accessible to all and profitable to the providers at the same time?
HPE is one company that has made significant strides in this regard by embracing the twin doctrine of digital transformation and sustainability. Their customers can reduce their energy costs by more than 30% by eliminating overprovisioning through HPE GreenLake. In fact, their consumption-based offerings have reduced customer carbon footprint by 50% in one case. Minimizing e-waste is another area of focus for them too.
So what have we learned from all this? As an ancient Chinese proverb states, “When the winds of change blow, some people build walls, others build windmills.”
What will you build?
Article | January 4, 2021
2020 has been an unprecedented year where we have seen more downs than ups. COVID-19 has impacted every aspect of our lives. But when it comes to digitisation and Artificial Intelligence, we have seen some impactful developments and achievements. As we approach the end of 2020, it is worth to look back at these AI stories to highlight the truths and discuss what it means for AI future direction.
The Great Truth:
Artificial intelligence played a crucial role in the detection and fight against COVID-19.
Indeed, we have seen the emergence of the use of AI at hospitals to evaluate chest CT scans. With the use of deep learning and image recognition, COVID patients were diagnosed thus enabling the medical team to follow the necessary protocols. Another application was the triage of COVID-19. Once a patient has been diagnosed with COVID, AI has been used to predict the likely severity of the illness so the medical staff can prioritize resources and treatments.
COVID has highlighted the need to deploy intelligent autonomous agents. As a result, we have seen both robots used at hospitals to diagnose COVID-19 patients and drones deployed to monitor if the public is adhering to social distancing rules.
Another major AI contribution in the fight against COVID-19 is in the area of vaccine and drug discovery. Moderna’s vaccine that has been approved by US Food and Drugs Administration has used machine learning to optimise mRNA sequencing.
The above is a proof that AI can make great contribution to mankind if it is used for “good”.
The Glowing Truths:
Some impressive AI results have been achieved. However, to leap forward a holistic and sustainable approach is needed.
2020 has seen some great AI achievements and leaps forward. The first example is Deepmind’s AlphaFold. The model scored highest at the Critical Assessment of Structure Prediction competition. The algorithm takes genetic information as inputs and outputs a three-dimensional structure. The model has impressively addressed a 50-year-old challenge of figuring out want shapes proteins fold into known as the “protein folding problem”.
While Deepmind’s AlphaFold is a great achievement, it is noted by some scientists that it is unclear how the model will work with more real-world complex proteins. Thus, more work is needed in this area.
The second example is OpenAI’s GPT3. The model is a very large network composed of 96 layers and 175 billion parameters. The model has shown impressive results for several tasks such as NLP questions & answering and generating code.
However, it is noted that the model does not have any kind of reasoning and does not understand what it is generating. Furthermore, its large size makes it very expensive. It is also unsustainable carbon footprint wise; its training is equivalent to driving a car to the moon and back.
While both AlphaFold and GPT3 models are both impressive achievements, there are some philosophical challenges/ questions that need to be addressed/ answered. The first question is about games/ simulated worlds vs. real world examples. Most often algorithms/models succeed in simulated world but fail in real world as the environment is more complex. How can we close the gap? How can we make the AI models succeed with complex tasks? I guess the first step is to apply AI to a real-world example with varied complexity levels.
The second question is about the structure and the size of AI models. Do models have to be big? Can we come up with a new generation of algorithms/ models that are smaller is size and have more efficient computations? Well to answer this question we have to take a pause on deeplearning and explore new venues.
The Gross Truths:
Ethics and bias remain the main drawbacks of Artificial Intelligence.
Over the last year, we had several prominent examples of AI ethics and bias issues. The first example relates to facial recognition: after several calls against mass surveillance, racial profiling and bias, and in light of Black Lives Matter movement starting in the United States, several tech companies such as Microsoft banned the police from using its facial recognition technology.
The second example relates to the use of an algorithm to predict exam results during COVID-19 period: after accusations and protests that the controversial algorithm was biased against students from poorer backgrounds, the United Kingdom government was forced to ditch the algorithm.
In the absence of regulations and tightened frameworks, ethics and bias will continue to be the main concerns surrounding the use of artificial intelligence.
Looking into the future, AI adoption will continue to accelerate, and we will probably see more breakthroughs achieved by only if we start looking at the subject in a holistic and sustainable view. Focusing models on real world problems and reducing the models carbon footprint will be a major step forward. We need to move away from thinking that “more” is always “more”. Sometimes “more” is “less”.