Everything You Need To Know About
AI Transformation
AI Transformation has taken the world by storm. There are discussions and deliberations about AI everywhere around us. So, we at Kenyt.ai have put together this page as a on-stop solution to all your queries related to AI transformation.
Scroll through the various topics and gather information that can help you create an impact in your business. And before we get into the article, we request you to be wary of any inadvertent mistakes that might have crept into the content. We request your support towards making this piece even more engaging with suggestions for topics and improvement ideas.
AI transformation refers to the strategic innovation through which businesses apply Artificial Intelligence in their business.Â
By incorporating AI to their daily working, businesses can simplify complex workflow. The incorporation of AI in business activities.
This transformation plays a crucial role in eliminating redundant activities for various employees and helps in completing typical tasks with relative ease.
AI transformation streamlines workflow in various businesses by building a continuously evolving business model for agile working.
As technology grows rapidly, businesses have increased their reliance on AI significantly. This is because AI provides them with a solid ground to enhance their offering to the users. The manual workload on the employees are lowered and the responses are more accurate and effective. Internally, too, AI has the ability to manage workflows effectively and help in getting work done within a stipulated time.
Let us briefly explore the importance and the benefits of AI transformation on various businesses.
Just like the wise saying – “Every coin has two sides”, AI transformation also comes with certain challenges and disadvantages. The most common and alarming challenges are as follows.
6. Accountability and decision-making
In the upcoming section, we will discuss the characteristics of AI transformation and how to overcome these challenges. You will learn how to potentially use AI to transform your business with a positive outset.
AI has not come to the fore in less than a decade. In fact, AI has been under development since ages. This timeline will provide you with an idea of the various stages in AI development.
Just like any other technology, there are certain technical terms that are repeatedly used when it comes to conversations related to AI. Lets us quickly learn a few of the basic terms that we are most frequently going to encounter when dealing with AI transformation.
Machine Learning (ML) is a branch of Artificial Intelligence that can identify patterns, learn from data, and even make decisions on its own. With the emergence of big data, it becomes easy to train system with detailed information with minimum interference from humans and other systems. Although Machine Language is a buzz work today, it has always been in existence since a very long time.
This technology is becoming so popular with each passing day. It is a matter of fact that you are using ML everyday in your regular day-to-day activities. The recommendations you get on Amazon Prime, or Netflix, the suggestions of various people you get on Facebook or LinkedIn is all possible with ML. Even voice assistants such as Siri, Alexa, and others also use ML for managing responses.
Deep learning is a part of Machine Learning that serves as the cornerstone for revolutionizing the way machines and systems work. In simple words, Deep learning can be symbolized with our neural system. The intricacy of our neural system is utilized in computer systems to generate results that are human friendly.
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This transformative approach has unlocked new horizons in healthcare, education, research, and various other fields. A Deep neural network generally consists of multiple layers of neurons that process input and generate a desired output as per required by the user. Deep learning systems can be in the form of supervised, unsupervised, as well as reinforcement machine learning systems. However, data availability and long installation time are the top challenges in Deep learning systems.
Natural Language Processing (NLP) is also a part of computer science and Artificial Intelligence that provides computer system to understand and interpret human languages. This system allows computer systems to understand input in the form of text and speech. NLP works on the principle of combining computational linguistics together with statistical modelling, Machine Learning, and Deep learning.
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Natural Language Processing plays a crucial role in improving the productivity of employees and simplifying critical business processes. You can approach NLP with three different approaches, namely - relu-based NLP, statistical NLP, and Deep learning NLP. However, vocabulary, training bias, voice tone, and misinterpretations are common challenges faced in NLP systems.
Computer vision is a field of Artificial Intelligence that helps computer systems analyze and learn from visual images. This process helps in extracting information from images, videos, and other visual inputs. The system is then able to take corrective actions in case of issues or identify defects.
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Basically, computer vision lets a computer to see, just like AI lets a computer think. This is very similar to the vision of humans, however, the only advantage for humans is the head start. Computer vision requires a lot of data for training. For instance, if you want a computer system to identify defects in a automobile tire, it should be provided with numerous images of tires.
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Ethics refer to a set of principles and guidelines that discern the functioning of a certain system. Similarly, AI ethics help us discern the right from the wrong. This helps us in making AI system effective, helpful and minimize the usage of such technology for non-helpful deeds and other risky or adverse outcomes.
AI bias refers to the occurrence of biased results that pop up due to human negligence during training. This results in distorted and potentially harmful outcomes. You should take due care to ensure the complete accuracy and prevalence of AI results. AI bias can result in mistrust and scandals that can cause severe damage to the overall functioning of the environment and surroundings.
AI transformation helps in simplifying the workflow in various departments. This is possible through an effective implementation of AI. Let us explore the impact of AI in various departments.
AI transformation helps you in automating repetitive activities in marketing. Further, personalization and customization of various tasks are also possible when using AI. The role of AI in marketing can be summarized as follows
AI comes in handy for the sales team and eliminates the various factions of misunderstanding and lost leads. With the effective help from AI, you can quickly convert leads and follow up with clients, thereby keeping a high engagement rate.
In short, AI plays the following role in sales AI automation-
When it comes to support automation, AI plays the key functional role of solving incoming queries instantly. This eliminates delays and increases the engagement of the users significantly.
The role of AI in customer support automation is as follows-
A key department where AI plays a key role in the HR department. AI not only limits its presence to existing employees, but also involves in the hiring process. This helps HR professionals hire candidates, automate the onboarding process, and solve repetitive queries related to compliance, leave policy, and other such things.
In short, the role of AI in HR can be summarized as followsÂ
As AI transformation takes over, the impact of copilot is witnessed in various workspaces. The primary features of AI copilot are as followsÂ
Further, AI copilot offers you various significant advantages. A few of the top advantages are as follows
AI plays a key role in various industries, assisting professionals in their day-to-day activities. In this section, let us understand the role of AI in various industries
This is a crucial industry where AI has made clear inroads. With AI transformation, healthcare professionals can provide effective treatment and identify various ailments with ease. In short, the key role of AI in healthcare can be summarized as follows
AI Transformation is assisting financial institutions and fintech industries to come up with enhancements to enhance security and protective measures. In addition, AI is paving a crucial way for providing customized and personalized options for various users. This increases the trust of the users in the industry and, therefore, increase the revenue flow. The major role of AI in financial institutions is as follows -
AI transformation is key to simplifying supply chain management. This helps the retail industries to provide customers with enhanced experience. From personalized shopping suggestions to managing stock replenishment, AI is a win-win solution for both customers as well as businesses. The primary role of AI in retail businesses can be listed as follows -
AI is not only limited to software and computer based industries. Large as well as medium manufacturing industries have already incorporated AI to their working method. AI has proven to improve the quality and safety conditions in various manufacturing facilities. The applications of AI in manufacturing industries include -
Convenience and optimal route planning is a key aspect for the transport industry. Whether it is logistical support for major events or transporting resources, AI improves the planning process and provides customers with improved comfort and satisfaction. The role of AI in the transportation sector can be summarized as follows
When it comes to AI transformation, we cannot ignore its role in transforming education. Both aspects of teaching and learning are improved, therefore, building a future that is capable and talented.
Are you feeling that you have been left behind in this race for AI glory?
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AI transformation is all about incorporating and implementing AI at the right time in your business or industry. If not done properly, this could eventually result in loss of time, efforts, and money.
This section will provide you with the basic fundamentals that will assist you through the process of AI transformation. The use and application of AI depends on the nature of your business and cannot be forcefully implemented.
The following steps are the key to a smooth and simple AI transformation procedure.
One of the key aspects of AI transformation is defining your needs and expectations. Your business should have a clear definition of what AI transformation will bring to the company. A clear strategy along with an effective roadmap will help you overcome challenges in implementing AI in your business.
Further, you should define measurable objectives for your business before you start incoproating AI transformation in your business. You should focus on minimum turbulence and improved customer satisfaction throughout the process.
AI transformation relies heavily on data. You should build robust data infrastructure that has the ability to collect and securely store large volumes of data. This will contribute to understanding trends and patterns with ease.
Further, advanced infrastructure will help you build effective systems with Generative AI functionalities. This will help you generate effective outcomes and building a workforce that understands the positive impact of AI. Further, an AI-ready infrastructure will offer an organization with greater potential towards work.
You need to plan and adopt an ethical AI practice to ensure that the data collection process is as per the pre-defined guidelines in your geographical area. Standard data management and integration is necessary to eliminate bias, build customer trust, and remove errors in the datasets.
Further, while integrating AI systems to your business, you should ensure that you prioritize data quality and governance principles. This is necessary for businesses to cover the full data lifecycle and build responsible systems.
Pilot projects serve as small stepping stones that help you incorporate AI technology effectively. With rapid and frequent changes to the AI environment, it is not advisable to make drastic changes to the regular functioning of your business infrastructure.
Take up small pilot projects and test changes before incorporating them in the system. These scenarios will also help you to build, learn, and adapt a strategy that will be the best suited for your business. Further, you can eliminate major risk and scale up your AI transformation with ease.
Now let’s come to the million dollar question – Will AI cause unemployment?
There has been a worrying trend that AI will replace the human workforce, resulting in massive layoffs.
Let us now decode this and understand the impact of AI transformation on the workforce.
The application of AI in the workforce has incredible and diverse options that are certain towards building a valuable future. This will build an environment for humans and AI to work together in harmony.
AI can play a role in selection, onboarding, and continuous evaluation of employees in various businesses. With AI, employees can save time and effort by avoiding the need for working on redundant and repetitive tasks.
Although the possibility of mass layoff still looms large, let us look at the positive outcomes of AI on the workforce.
As stated above, the impact of AI can be both exciting and apprehensive. AI can help improve productivity and lower the operation cost for various businesses and industries. However, it should also be noted that AI can result in job displacement and layoff. There is a very fine line of balance between AI and the human workforce. Industries and businesses that are capable of unlocking this line have the ability to improve their overall productivity. Employees will have to upskill and improve their skill set in order to work in tandem with AI. This human-AI collaboration is possible only with advanced problem-solving skills and data analysis.
While incorporating AI to the workforce, employees will have to upskill. In some cases, employees will have to reskill certain factions for a harmonious working environment with the AI. Highly skilled labor will provide businesses with accurate and consistent performance and increase the overall revenue flow and customer engagement. AI transformation will provide you with the ability to fine tune your employees for continuous development and optimization. This is possible with an automated feedback mechanism. By providing your employees with opportunities to enhance their skills, you can build an efficient workplace. Employees will understand and work in accordance with the changing and flexible conditions of the surrounding.
Generative AI is the wide and common example of human AI collaboration in real-life setting. Companies use AI to interact with customers and understand their trends and patterns. This provides your employees with a range of business settings and roles that come under the umbrella term of Generative AI. When AI and humans work in harmony the productivity and decison-making capability are increased significantly. The system learns new processes continuously and implements them in upcoming interactions for the overall improvement of the system. A collaboration between AI and humans happens when the industry feels the need for human interference in every stage. This is most commonly seen in the healthcare industry. There is AI for guiding patients through a certain procedure. However, each step is also assisted with assistance from a medical practitioner. This ensures safety and reliability of the system.
AI has suddenly taken center stage in recent times. With continuous innovation and transformation, AI is playing a crucial role in various different businesses and industries. However, like other systems, AI should also be kept under check for obvious reasons. For fair inclusivity and eliminating bias, various measures have to be taken. In this section, we will discuss the basic governing factors for AI. These steps ensure that AI transformation stays true to its useful benefits and does not result in harmful impact on people and the surroundings.
Ethical considerations are the basic foundation for the development and deployment of AI systems. By addressing bias, privacy, safety, human-centric designs, algorithmic governance, and transparency, developers can ensure AI transformation is ethically fit.
Companies have deployed teams to understand the practical inclusivity of AI in various domains. This data will help in training and implementing AI with confidence. Various governments are also coming up with policies and regulations to ensure the smooth functioning of the systems.
The UNESCO, along with the Global AI Ethics and Governance Observatory, have set up an observatory to monitor the progress and performance of AI in various business sectors and factions. This observatory studies the readiness and acceptance factor of various countries and its people towards AI transformation.
In 2021, 193 countries adopted the Recommendation on the Ethics of Artificial Intelligence that has been based on the observations of the UNESCO’s work on AI ethics and governance systems. This Recommendation mandated UNESCO to assist member nations with tools and resources to build a comprehensive picture of the preparation towards implementing AI for their citizens.
Bias happens due to incorrect training either intentionally or unintentionally. Such bias can result in hate and affect the sentiments of certain sections of society. To avoid such bias, AI transformation should thrive on the policy of fairness.
Bias can also result due to algorithms. The AI algorithms are designed in a certain way for equivalent inclusion of every aspect. However, if a certain faction of society is not covered under this algorithm, it results in bias with the system not favoring that faction. Care should be taken to eliminate such bias.
An example of such an incident came to the fore when the AI system was not able to identify dark skinned people, just because the system was trained with light skinned people.
AI increases the engagement of the users with the system. However, this results in the users sharing certain private and sensitive information with the system.
This underscores the need for a safe and secure system. Ensuring the privacy of your users is essential for building trust and loyalty.
Further, securing sensitive and confidential information is essential to prevent data from being misused.
Unlike other compute systems, personal data is collected and stored for continuous improvement of the system. AI systems use personal data for personalization and understanding the trends. Data privacy should be defined to ensure that data is stored and used in a secure methodology. Businesses should ensure that user data and information are not used without prior permission.
However, with the introduction and implementation of strict mechanisms, you can create a future where society and users benefit from AI. With clear policies and procedures from various different governing authorities, AI-based systems are continuously monitored. This helps in building a transparent system with increased engagement and loyalty.
When it comes to best practices for data security, you can adopt the following protocols. This will improve the security and provide for a smooth engagement with various users.
End-to-End Encryption of data
Multi-factor Authentication
Role-based Access Control
Data Masking
Enhancing cloud security
Data retention policies
Secure coding standards
Regulatory compliance
Awareness programs
Contract and agreements with 3rd party developers and associates
AI Transformation is here to stay. Businesses and industries that do not adopt this trend may fall short in terms of growth and achievements. In this section, we will discuss the future and emerging trends in AI that will change the functioning of various businesses and industries. One of the most prominent examples of AI is the development of powerful virtual agents. With advanced technology, these virtual agents have the capability to solve even the most complex queries instantly.
Further, users are able to get responses immediately that let them make decisions quickly. This further leads to an increase in revenue generation and business boom.
Although AI transformation is making buzz at the moment, there are still other AI technologies and innovations that are emerging from AI. These technologies and innovations, together with AI, help in building an environment for all-round development and growth.
A sneak peek into a few of the top emerging technologies and innovation include –
GPT-4
Chatbots and virtual assistants
Predictive AI analytics
Natural Language Processing (NLP)
Explainable AI (XAI)
Generative Adversarial Networks (GAN)
Even as more than 54% of global consumers incorporate AI into their daily routines, the predictions for the future impact of AI are simple and clear. This number of users currently relying on AI keeps on increasing. It can also be predicted with confidence that by the end of this decade, more users will possess personalized AI assistants that are personalized for individual needs.
Further, the integration of AI in various businesses and industries is anticipated with much fanfare. Professionals and experts believe the excitement surrounding generative AI and AI transformation could significantly lower the cost of AI technologies. Therefore, this will open new avenues for the growth and spread of AI across various spectrums.
Now that the AI transformation is a practical possibility, it is high time for you to start preparing yourself for this drastic change. You should not be left behind in this race for glory. In this section, we will explore the methods that will help you stay ahead of the race and master the art of AI transformation with glory and ease.
Preparation starts with simple steps that can be summarized as follows –
Prioritize AI literacy
Master the art of continuous learning and development
Establish psychological safety
Nurutre innovation and creativity
Encourage collaboration and team work
Build a flexible work schedule and set up
Personalize AI experiences
Set up ethical AI practices and guidelines
As far as AI Transformation is concerned, there are many challenges that can crop up during the incorporation process and even during various different stages. It is necessary for various businesses and industries to strategically overcome all such challenges for the overall smooth functioning.
In this section, we will discuss a few of the top challenges and methods to overcome such challenges.
Technology and the lack of efficient infrastructure are the most common challenges that come up when a business or industry takes up AI transformation. However, you will require effective and advanced infrastructure to incorporate AI in your daily work schedule.
AI relies on a large volume of data. So the primary necessity is storage with ample security to ensure safe and best practices. Further, these infrastructures do not come under one-time investment. Each of these systems have to be continuously upgraded and improved for continuous scalability.
AI transformation relies heavily on organizational and cultural differences in your workplace. Your employees and users should accept this AI transformation for a complete and smooth conversion. In case of sudden uprising or other such issues, the overall transformation process can go off-track.
Further, in some cases, consumers do not have the necessary expertise and knowledge to access certain functionalities in AI. You should take up the necessary steps and initiative to provide training to all your stakeholders. When they are confident to accept and implement AI workflow, the overall impact of the transformation also makes sense.
Additionally, employees have this fear of AI replacing their work. Hence, you should create a fearless environment and ensure that employees work in harmony with AI for increased engagement and productivity.
The legal requirements and regulatory bonds are variable across different places and geographical locations. This is because different governments have different regulations related to AI. While certain countries are open towards an inclusive AI concept, other governments have sanctions. You should also follow the protocols in order to thrive in specific demographic locations.
In addition to security and privacy issues, there are also issues related to transparency, inclusivity, and bias. So developers and AI platforms should ensure that they include various different training modules in the process to ensure efficient programming of their AI systems.
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Now that we have understood AI transformation, let us now understand the methods to bring about a transition in your business workflow. This section will help you choose the right tools and also provide few examples for platforms that are related to most common fields and their applications.
Let us take a look at some of the top AI platforms with various different applications and niches. This will help you in choosing the right tool for your business or industry.
Are you in search of a tool that will automatically engage with your clients on various different platforms?
Kenyt.AI is designed to improve the productivity of your customer support or sales team. By deploying chatbots on different platforms, you can improve engagement rates and lead conversion. This voice bot can be used by various different businesses and industries like healthcare, manufacturing, tourism, HR, and many others.
This is a chat based platform that serves as a Generative AI platform. This platform serves as a source of ideas for content creation and even for text to image visualization. Users can use this platform to understand and learn new concepts. With wide spectrum, this platform provides users with the ability to view different perspectives.
If you are looking for an AI-powered workflow management tool, ClickUp is your go-to choice. With ClickUp you can manage workflow and use the native functionalities to assign, delegate, and manage projects with ease.
The criteria for selecting various tools depends on your typical business requirements. As we discussed earlier in the implementation for AI, you will have to  identify business needs and opportunities, build an AI-ready infrastructure, develop and build effective data management and integration structures and then eventually start with  pilot projects and scaling up .
These steps will serve as a fool-proof method and help you select the right tool as per your requirement.
To understand the success of any new innovation, you will have to measure the performance. In such cases, you will require to implement KPIs and other techniques to understand the real value of AI in your business.
To calculate the KPIs of various metrics, you need to incorporate the following metrics in your system. The following metrics will help you evaluate KPIs and take necessary actions to continuously improve the processes.
In order to effectively incorporate the following metrics, the following steps will help you achieve these challenges:
Since AI relies on a large volume of data, trend analysis, and user data, the process of continuous improvement and optimization goes hand in hand. As there is a shift in the paradigm, AI systems should understand changing user preferences’ will help your system to be relevant and continuously engage with customers.
With this, we will wind up the learning phase for AI transformation. Let’s innovate and incorporate AI in our day-to-day life.
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