In an exclusive interview with TimesTech, Sameet Gupte, Co-Founder and CEO of EvoluteIQ, discusses the transformative impact of AI across various industries, the rise of intelligent business automation, and its significant contributions to sectors like healthcare and finance. Gupte also addresses the challenges of AI implementation, ethical considerations, and the future trends shaping the digital landscape.
Read the full interview here:
TimesTech: In your experience, how has AI been a game-changer across different industries and which sectors do you believe have benefited the most from its integration?
Sameet: Despite AI technology not being entirely new, we have seen its increased awareness, use, and adoption in the past couple of years. AI proves to be revolutionary in most industries today, as it brings better performance, decisions, and ideas to the table. Some of the key sectors where AI has made a significant impact are:
1. Healthcare: The new innovative diagnostic tests, individualized treatments, and better bureaucratic management of healthcare organizations.
2. Finance: Higher security level, better understanding of the investments, and better customer satisfaction.
3. Retail: Advancements in technological possibilities around inventory control, personalized shopping, and general inventory management.
4. Manufacturing: Enhanced efficiency, reduced downtime, and improved quality control.
5. Transportation and Logistics: Self-driving cars, route optimization, and fleet management.
AI is growing and is set to spread even to those areas not yet explored, with better future inventions and returns in the industries.
TimesTech: Can you elaborate on the concept of intelligent business automation and how it is revolutionizing traditional business processes?
Sameet: Intelligent Business Automation refers to the practice of using advanced technologies like Artificial Intelligence (AI), Machine Learning (ML), Robotic Process Automation (RPA) and Natural Language Processing (NLP) to automate complex business processes. It is not like traditional automation which was rigid with a more mechanical approach that saw robots perform routine work.
A firm’s components of intelligent business automation strategy involve the following:
- Robotic Process Automation (RPA): This involves task automation and integration.
- Artificial Intelligence (AI) and Machine Learning (ML): Analysis of data collected and identifying trends and patterns for organizational decision-making improvement.
- Natural Language Processing (NLP): Helps machines understand human language better, thus enhancing customer care and automating tasks such as sentiment analysis and documentation.
- Process Mining: Includes studying the way in which processes operate; one is in a position to notice areas of weakness and directly improve the flow of work.
Intelligent business automation is the key concept that has extended modern business processes changing their traditional work model to become intelligent, accurate, and progressive. But, as these technologies remain to be developed, there is much potential with respect to new advancements and enhancement of business procedures.
Enhanced Efficiency and Productivity:
- Automating Repetitive Tasks: By automating everyday tasks, employees can focus on higher-value activities that need creativity and strategic thinking.
- 24/7 Operations: Automated systems can work around the clock, increasing productivity while reducing lead times.
Improved Accuracy and Reduced Errors:
- Cutting Down Human Error: Automation minimizes the risk of errors in data entry, calculations, and other tasks commonly plagued by human error.
- Consistency: Automation guarantee uniform execution of tasks, leading to more consistent outcomes.
Cost Savings:
- Labor Costs: This ensures a decreased demand for physical work due to automation which leads to substantial cost savings.
- Operational Efficiency: Businesses can streamline processes and reduce waste thus reducing operational expenses.
Scalability:
- Handling Volume: Automated systems can easily scale to manage high volumes of work without a relational increase in budgets.
- Adaptability: IBA systems can be adjusted to the needs of the business as well as explicit changes in the market setting in a short period.
Enhanced Customer Experience:
- Personalization: Customer data can be processed by using AI to recommend services and offer individual solutions to customers.
- Quick Response: Improved customer satisfaction as chatbots provide immediate answers to customer questions and queries.
Data-Driven Decision Making:
- Real-Time Insights: IBA tools offer real-time analytics and insights, enabling faster, more informed decision making.
- Predictive Analytics: AI can assist businesses in forecasting trends and results better for efficient planning and strategizing purposes.
Compliance and Risk Management:
- Regulatory Compliance: Automation guarantees that processes align with regulatory standards, lowering non-compliance risk.
- Risk Mitigation: Automated systems can pinpoint and mitigate risks by observing transactions and determining suspicious activities.
TimesTech: How is AI, particularly intelligent business automation, improving patient care and operational efficiency in the healthcare sector? Can you share some real-world examples?
Sameet: There has been a big increase in AI, especially Intelligent Business Automation (IBA), which is used in healthcare to improve patient service and enhance operational efficiency. Here are some ways AI and IBA are influencing the medical industry, with examples from real life:
Enhancing Patient Care
- Diagnostics and Imaging:
AI-Powered Imaging: Diagnostic imaging such as X-rays, MRIs, and CT scans are analyzed with greater accuracy with the help of AI algorithms to diagnose several diseases at an early stage.
Example: A few of the AI solutions that are employed in hospitals have helped diagnose breast cancer from mammograms. It has been found that it has reached extremely high accuracy, sometimes even higher than that of human radiologists.
- Personalized Treatment:
AI-Driven Insights: AI helps analyze patient records and propose individual therapies with reference to their genetic profile and medical history.
Example: A leading hospital in Canada is assisting its oncologists by providing various treatment plans for cancerous patients based on clinical research of basic profiling of patients.
- Virtual Health Assistants:
Chatbots and Virtual Assistants: Virtual health assistants powered by AI simplify the task of answering patient’s questions, appointments, and even prescription renewal.
Example: A leading health and wellness company in the USA is utilizing AI to provide a customized assessment of their symptoms/illness and guide the patient as to the right action to take – to self-treat or seek medical assistance.
Improving Operational Efficiency
- Administrative Automation:
Streamlining Processes: Specifically, IBA helps minimize repetitive tasks like scheduling patients’ appointments, billing, processing claims, etc., as these responsibilities can be automated and will help reduce the overload of healthcare workers and reduce human error.
Example: A government hospital that operates at the highest level in Europe has adopted automated interfaces that handle routine administrative procedures such as prior authorization, pre-authorizations, and payments while freeing up manpower to care for the patients.
- Supply Chain Management:
Inventory Optimization: AI predicts demand for medical purchases and helps replenish the stock, ensuring that the hospitals have the necessary stocks without major excesses.
Example: A major healthcare organization in North America employs AI to manage and improve its inventory control, making sure that requisite medical stocks are available, hence minimizing waste as well as costs.
- Predictive Analytics:
Resource Distribution: AI models predict the number of admissions and the corresponding consumption rate for all resources, allowing hospitals to manage the workforce and beds more efficiently.
Example: A well-known clinic in the central USA uses AI to predict patients’ admission and allocate beds to indicate patient throughput and minimize waiting times.
TimesTech: What are the primary challenges organizations face when implementing AI-driven solutions, and how does EvoluteIQ address these challenges?
Sameet: Implementing AI-driven solutions presents several challenges for organizations from having an integrated technology platform to having a team with the right mindset of adopting change.
The EIQ Platform is a leading End-to-End AI-enabled Intelligent Business Automation platform with a core fabric of Generative AI. The comprehensive platform simplifies the automation of complicated business processes by leveraging its integrated modules of RPA, ML, AI, Data Flow, Work Flow, Event Flow, 3000+ Connector libraries, IoT, and Blockchain, along with its Low Code/No Code functionality.
The central challenges involved in the implementation of AI-driven solutions and how EvoluteIQ addresses them are:
- Data Quality and Management
Challenge: The success of AI models depends on the availability of good quality data that is updated, relevant and clean. Consequently, poor data quality can cause AI models to generate wrong insights and predictions.
EvoluteIQ’s Approach: The EIQ Platform pulls together data from different sources, ensuring uniformity and quality of information. It has tools for cleaning, mapping, conversion, and enrichment, which are all necessary for effective AI deployment.
- Integrating with Existing Systems
Challenge: Integrating AI solutions into existing IT infrastructure and legacy systems may be intricate, time-consuming, or a stumbling block to adoption since many customers do not want to throw away their investments in other systems.
EvoluteIQ’s Approach: However, EvoluteIQ’s system is fully non-intrusive, so it can fit well into already existing systems. The platform supports various integration protocols and APIs with over 3000+ connector libraries, making it easier to connect disparate systems.
- Scalability
Challenge: Scaling AI solutions to handle enormous amounts of data and transactions can be quite challenging as the company expands.
EvoluteIQ’s Approach: The EIQ Platform is scalable so that as companies grow, they can accommodate more data and transactions without compromising performance. It has a strong infrastructure and cloud support for scalability.
- Skill Gaps and Talent Shortage
Challenge: The lack of talented workers who can develop, deploy and manage AI solutions will slow down implementation.
EvoluteIQ’s Approach: Low-code/no-code platforms like the EIQ Platform allows business users and non-technical individuals to be able to create and control AI-based systems effortlessly. This democratizes the technology and minimizing dependency on specific AI expertise.
- Cost and Resource Allocation
Challenge: High cost of implementing AI solutions might arise due to huge investments in technology, infrastructure, and manpower.
EvoluteIQ’s Approach: By integrating RPA, AI, ML and Data Integration into one platform, multiple tools are avoided, resources streamlined while costs are reduced.
- Change Management and Adoption
Challenge: New AI-driven processes are difficult to be adopted by teams for effective use. This is due to their reluctance to change.
EvoluteIQ’s Approach: The EIQ Platform aids in managing changes through its user-friendly interface and comprehensive training support. In this way, it facilitates the ease of transition as one adopts AI-driven processes.
- Security and Compliance
Challenge: Security of data and regulatory compliance is important when implementing AI solutions.
EvoluteIQ’s Approach: The EIQ Platform features strong security measures such as data encryption capabilities, access controls as well as compliance management tools. This ensures that companies meet statutory requirements and protect sensitive information.
- Measuring ROI
Challenge: Proving ROI on AI projects is not always easy because its advantages may not be instantaneously apparent.
EvoluteIQ’s Approach: The EIQ Platform has analytics and reporting features that can help measure the effects of AI-driven solutions. By these means, organizations can monitor performance metrics and appreciate the value delivered by such initiatives, thereby demonstrating ROI.
How EvoluteIQ Addresses These Challenges?
EvoluteIQ’s EIQ Platform, designed for intelligent business automation and integration, offers several features to overcome the challenges of implementing AI-driven solutions:
• Unified Platform: Integrates RPA, AI, ML, and data integration into one platform, thus cutting costs and complexity in an organization.
• Low-Code/No-Code Development: This makes the journey of designing and deploying algorithmic solutions easy for users from a non-technical background.
• Data Integration and Management: Helps to obtain high-quality data and its possibility of integration into existing systems.
• Scalability: Scales well with an organization’s size, requires less frequent adjustment, and is more stable with respect to changes in business size.
• Security and Compliance: Includes a strong security and compliance system to meet the required levels of information protection.
• User-Friendly Interface: This makes its adoption rather easy by virtue of an understandable interface and numerous resources available to the client.
• Analytics and Reporting: Provides resources for comparing the success rate and ROI of AI solutions in an organization so that the results are evident.
When managing such challenges, EvoluteIQ allows organizations to deploy AI and other business-enhancing solutions within the shortest possible time to improve operational performance and enhance decision-making.
TimesTech: What are some emerging trends in AI and business automation that you foresee having a significant impact in the next five years?
Sameet: There are several emerging trends that can be established within the next five years in AI which will change the shape of various industries. Among major trends is the infusion of AI and IoT – making systems smarter, and more interconnected for improved efficiency parallel with predictive maintenance. This is leading to the trend of hyperautomation or intelligent business automation, where advanced AI tools – including ML, RPA, etc. work together to automate end-to-end business processes, bringing unheard productivity and agility to the work. Content creation and design will also be redefined with the help of Gen AI for personalized, novel solutions. Also, the rise of ethical AI and transparent AI governance will become increasingly important to ensure the responsible and equitable application of technology.
EvoluteIQ is at the vanguard of these trends, always looking for ways to innovate our platform to exploit these advancements, ensuring that our clients stay ahead in the rapidly maturing digital market.
TimesTech: With the rise of AI, there are concerns about its impact on the workforce. How can businesses balance automation with human employment, and what role does EvoluteIQ play in this dynamic?
Sameet: Today’s business landscape is so quickly changing that it has also become indispensable to balance automation with human employment. We at EvoluteIQ see AI as a power that makes humans stronger and not as a tool that can replace them. This can be achieved by letting the machines take care of monotonous work and have the employees focus on strategic, creative, high-value activities. This holistic approach improves output – but more importantly, it encourages innovation and significantly strengthens employee satisfaction.
EvoluteIQ is working in this space by providing intelligent automation solutions, that work closely with the workforce. By deploying AI to automate repetitive work, organizations can effectively upskill their existing workforce creating a culture of lifelong learning and change. This ensures sustainable growth and a workforce that is future-ready, in conformance with the fundamental principles of Industry 5.0.
TimesTech: What ethical considerations should companies keep in mind when deploying AI technologies, and how does EvoluteIQ ensure responsible AI use?
Sameet: When it comes to the implementation of AI technologies, ethical concerns are crucial. The responsible use of AI requires companies to focus on transparency, fairness, and accountability. We follow these principles at EvoluteIQ by incorporating ethical considerations into our platform design and deployment processes.
We ensure AI systems are transparent by making their decision-making processes understandable and traceable. We also test our algorithms thoroughly to avoid biases and guarantee fair outcomes for all users in the system. Regular audits ensure accountability and compliance with industry standards & regulations.
We also place importance on data privacy and security, going the extra mile to shield user details with strong safeguards. This includes establishing an ethical culture within our team and educating regularly on responsible AI practices. This way, EvoluteIQ is able to maintain the ethical considerations on top and introduce AI solutions that enable innovation along with trustful compliance.
