Thursday, June 13, 2024
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PIONEERING TOMORROW: ANUPAM ANAND’S ASCENDANCY IN AI LEADERSHIP

In the world of AI, one name shines as a model of innovation and leadership: Anupam Anand, Vice President at Apptad Inc. Certified Digital Transformation Leader (from IIM Lucknow) and With more than 20 years of experience and enthusiasm for making use of AI (GenAI) to solve real-world issues, Anupam has made significant contributions to the profession by leading distinguished projects and pushing forward natural language processing as well as other machine learning models. Anupam has received two Bronze awards for excellence in Enterprise Automation Project Delivery and has also been honored with the Innovation Marathon Award.

His journey has been characterized by uncompromising commitment to excellence, passion for lifelong learning, and an unwavering adherence to ethical principles in AI development. In this exclusive interview with CEO Review Magazine, Anupam provides some insight into his journey, experiences and future vision on AI that will guide professionals and organizations as artificial intelligence evolves swiftly. Since we enter the mind of a true artificial intelligence chief while exploring what lies ahead in a transforming industry.

Table of Contents

Anupam, it’s a pleasure to have you with us today. Can you provide our readers with an overview of your background and experience in AI?

Thanks for having me here. I began my AI journey during my professional work around 4-5 years ago, which has accelerated since I joined Apptad in May 2021. My focus has been on deep learning and more on natural language processing (NLP). I run major AI initiatives at Apptad, where I am engaged in developing various predictive models and a recommendation engine that boosted customer engagement. Moreover, I’ve utilized Generative Adversarial Networks (GANs), reinforcement learning, and explainable AI on various projects. Now, I lead an AI research team at Apptad, exploring AI/GenAI-based applications in Healthcare, Fintech, and Supply chain , while emphasizing ethical AI practices.

What motivated you to pursue a career in AI, and what keeps you engaged in the field?

My initial fascination with AI stemmed from its potential to revolutionize industries and improve lives through intelligent automation and problem-solving. What keeps me engaged is the dynamic nature of the field – there’s always something new to learn, discover, and apply. To stay updated, I regularly attend conferences, participate in online forums, and engage with academic literature. Additionally, I’m involved in professional networks and collaborate with peers to exchange insights and stay abreast of the latest advancements and trends in AI.

Can you discuss a particularly challenging problem you solved using AI, and the approach you took to tackle it?

I’ve tackled various promising challenges in client projects, contributing to the development of AI tools. However, one current in-house project for our talent acquisition department truly stands out. We aimed to improve the hiring and filtering process using AI, addressing the tedious task of resume scrutiny for recruiters. Our goal was to simplify and speed up this process while identifying the most suitable candidates. Currently in the pilot phase, we began by collecting a wide range of resumes aligned with job descriptions (JDs). We manually annotated these resumes with relevant attributes and then applied natural language processing techniques to preprocess the text data and extract essential information. We trained machine learning models on this annotated dataset to classify resumes according to predefined criteria. Using indicators like accuracy, we iteratively refined these models based on feedback from our recruitment team. Although still in the pilot phase, we aim to finalize it by the end of this month or next.

What are the key qualities you believe are essential for a successful AI leader?

In my opinion, a successful AI leader should possess a visionary mindset, strong technical expertise, strategic thinking abilities, collaboration and communication skills, adaptability, continuous learning habits, and a commitment to ethical and responsible AI practices.

How do you foster innovation and creativity within your AI team?

Encouraging creative and innovative culture in an AI team involves a number of approaches. To begin with, I advocate for experimentation culture whereby members are wel come to experiment with their ideas without fear of failure Secondly, I encourage cross-discipline partnerships by urging teams that have various specialists to work together. Thirdly, I avail resources for learning and development, whether courses or other educational materials that help augment the skill set of my team members. Fourthly, I reward creativity through public recognition and celebration of innovative ideas or solutions. Finally, I promote autonomy and ownership among my team members by allowing them the freedom to initiate personal projects within a specific scope while providing necessary support when needed.

Can you share your thoughts on the ethical considerations and potential risks associated with AI technologies?

Certainly, ethical considerations and potential risks associated with AI technologies are paramount. Bias and fairness, privacy and data protection, transparency and accountability, job replacement and economic effects, independence and responsibility, as well as safety and malicious use are among the major ethical concerns and risks connected with AI technologies. Coping up with these issues demands joint action among players from different quarters such as scientists, administrators, industry captains as well as the rest of the society.

What strategies do you employ to ensure AI projects are aligned with business goals and objectives?

To keep AI projects in line with the company’s aims and expectations, there are a few things I do. First is to continuously communicate with stakeholders to understand what they prioritize and expect from me. Second, I set clear objectives and KPIs for measuring the success of AI projects. Thirdly, I collaborate across departments so as to ensure that all stakeholders are bought into the idea. Fourth, I give priority to activities that have high value and also those which can be carried out successfully. Fifthly, my approach encompasses iterative development whereby feedback is obtained from stakeholders who are then incorporated into the system as need arises. Finally, performance monitoring and regular reporting aim at ensuring that projects remain focused on their intended purpose thus delivering value to the entire organization.

How do you approach the integration of AI solutions into existing business processes or systems?

Integrating AI solutions into existing business processes or systems involves several steps. Firstly, I assess current processes to identify opportunities for AI integration. Secondly, I select appropriate AI technologies based on the specific requirements of the business. Thirdly, I prepare and integrate data to train the AI models effectively. Fourthly, I pilot test the AI solutions to validate their effectiveness and identify any issues. Fifthly, I deploy the AI solutions into production and monitor their performance over time. Lastly, I provide change management and training to ensure smooth adoption and integration within the organization.

Can you discuss a time when you had to manage a project with conflicting stakeholder priorities or requirements?

Certainly. An instance was when I led a project to develop an e-commerce chatbot. The customer service, marketing and IT departments were the stakeholders. The department of customer care gave priority to efficiency and accuracy in answering customers’ inquiries while the marketing team wanted it to work as well as a promotional tool. Besides, the IT department had qualms on data safety and integration with existing systems. I facilitated meetings between representatives from each group of stakeholders so that they would tell us their needs and fears for better understanding. We found shared goals such as enhancing user experience or bringing down operational costs which helped aligning stakeholders’ points of interest. Then we looked into various solutions considering the priorities of every stakeholder group and adjusted the project’s scope and its features based on those who use it iteratively.

What role do you see AI playing in shaping the future of industries such as healthcare, finance, and transportation?

AI could be a game changer in the healthcare sector, finance, and transportation as it helps define the future. AI has transformed diagnosis treatment and patient care through improvements in medical scans, predictive analysis and individualized medicine. Fraud detection, risk assessment and customer service are some of the ways in which AI is changing the financial industry by improving security measures, efficiency rates and customer experiences. The use of AI in transportation is transforming this sector through self-driving cars systems, traffic control units as well as predictive maintenance that improve safety standards and efficiency of operations while also promoting sustainability. In summary, artificial intelligence can bring about innovation, efficiency improvement and high quality delivery of services across different sectors.

How do you assess the performance and effectiveness of AI models and algorithms?

AI models’ and algorithms performance examination and effectiveness demand a few main steps. Firstly, the evaluation metrics that I define should agree with the specific aims and objectives of the AI project such as accuracy, precision, recall, F1-score, and area under the receiver operating characteristic (ROC) curve. Secondly, I divide data into separatetraining and testing sets to assess how well my model performs with never seen before data. Thirdly, I use this training set for training my model which is then tested using these defined evaluation metrics in the test set.

Fourthly, I am optimizing performance by iterating on model architecture with hyper parameters and feature engineering techniques. Fifthly, there are other business related aspects of an AI system apart from just its performance metrics like scalability, interpretability , alignment with business objectives etc which must be considered also. Lastly, I put it into practice and keep watch over it till its stability period over time by having mechanisms in place to track KPIs while monitoring degradation in performance or drifts in data distribution patterns.

What are the biggest challenges you’ve encountered when scaling AI initiatives across an organization, and how did you overcome them?

Various difficulties go with the process of spreading out AI initiatives across an organization, such as data quality and accessibility, structure and resource constraints, talent and expertise, integration with existing systems as well as adaptation and change management. To come over these barriers, I have used a number of methods. Firstly; I have fostered collaboration among teams of artificial intelligence and other departments in the organization to harmonize AI initiatives with business objectives while addressing area-specific issues. Secondly; I have invested in strong infrastructure, tools, and platforms that facilitate growth, deployment, and scaling-up of artificial intelligence initiatives.

Thirdly; I have concentrated on governing data & its management so that data quality is ensured while at the same time privacy and security are maintained. Fourthly; investing in on-going training & development aimed at reskilling current staff while attracting to the company new talents who possess AI know-how. Fifthly; starting off with small pilot projects so that the value of artificial intelligence initiatives can be established together with building momentum within companies. Lastly: securing executive support plus sponsorship for company’s artificial intelligence (AI) programs so as to ensure they are consistent with organizational principles or strategies –thus allocating resources required for implementation/investment thereof.

Can you share your insights on the role of AI in augmenting human intelligence and decision-making?

Artificial intelligence (AI) can be used to expand human intelligence and decision-making in a number of ways. First, AI is capable of fast and accurate completion of massive amounts of information which can provide insights and offer recommendations for informed decision making. Second, AI could perform routine jobs leaving human employees with enough time to concentrate on high-value assignments requiring creativity, problem-solving abilities and critical reasoning. Third, AI helps personalize recommendations and guidance based on individual likes and preferences thus enhancing user experience.

Fourthly, AI enables forecasting using predictive analytics that enables organizations to forecast future trends, results or risks. Fifthly, AI improves decision support systems by providing real-time insights as well as supercharging the entire decision-making process. Finally, AI addresses ethical dilemmas encountered by acting as a watchdog for biases, errors made or ethical implications present in decisions being arrived at. Overall, AI has the potential to complement and augment human intelligence and decision-making capabilities across various domains thereby empowering individuals and organizations with knowledge required to make better decisions through improved efficiency leading to innovation.

LinkedIn recognized you with the “Top Artificial Intelligence (AI) Voice” badge. What advice would you give to others looking to establish themselves as thought leaders in artificial intelligence, especially in the realm of voice-related technologies? How can professionals leverage platforms like LinkedIn to showcase their expertise effectively?

Establishing oneself as a thought leader in artificial intelligence, especially in the realm of voice-related technologies, requires a strategic approach to leveraging platforms like LinkedIn. Firstly, professionals should focus on creating high-quality content that showcases their expertise and insights in the field. Secondly, they should engage with the AI and voice technology community by participating in discussions, commenting on posts, and sharing their perspectives. Thirdly, they should highlight success stories and use cases to demonstrate the real-world impact of AI and voice technologies, positioning themselves as knowledgeable and experienced professionals. Fourthly, they should stay updated on the latest developments and advancements in AI and voice technologies through continuous learning and education. Lastly, they should cultivate a strong personal brand that reflects their expertise, values, and unique perspective in the field of AI and voice technologies, attracting opportunities for career advancement and recognition.

How do you see the field of AI evolving in the next 5-10 years, and what opportunities do you foresee for organizations and professionals in this space?

In the next 5-10 years seems long though, with the pace its evolving within a year or so , people will witness the significant evolution and growth, presenting both challenges and opportunities for organizations and professionals. Advancements in AI technologies, integration of AI into business processes, expansion of AI applications, ethical and regulatory considerations, demand for AI talent, collaboration and partnerships, and AI-powered innovation and entrepreneurship are some of the key trends and opportunities shaping the future of AI. Overall, the next couple of  years hold immense promise for the field of AI, with opportunities for organizations and professionals to leverage AI technologies to drive innovation, solve complex problems, and create value in diverse industries.

What advice would you give to someone aspiring to become an AI leader/expert?

My mantra is – “Learn – Unlearn – Reskill” yourself. My advice to someone aspiring to become an AI leader/expert would be to invest in continuous learning, develop strong technical skills, gain domain-specific knowledge, build leadership and communication skills, embrace ethical and responsible AI practices, network and collaborate, and be persistent and resilient. By following these strategies, individuals can effectively navigate the dynamic and rapidly evolving field of AI and achieve success as leaders and experts.

Final Words:

It is a very good example of how you can make a real difference in people’s lives by being passionate about the things that you do. It’s really awesome to know his wisdom, his lessons and his futuristic views over AI; they are what inspire different organizations’ heads and as well as young professionals who have yet to make their way into this field. In the ever-changing world of artificial intelligence (AI), we must embrace the ability to influence it by making more intelligent, efficient and moral decisions. This has been a very informative interview, thanks Anupam Anand and CEO Review Magazine for having this talk with us and may your journey on AI continue to motivate & empower us all.

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