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According to a Gartner report, 80% of CEOs expect artificial intelligence (AI) to enhance corporate efficiency. Excerpts from an interview with Rakesh Ravuri, CTO and SVP – Engineering at Publicis Sapient, on the need of seizing this opportunity now, the ethics of doing so, and how AI will lead to the creation of new sorts of employment in the future.
How important is corporate digital transformation for businesses? How does generative AI help with long-term growth?
Firms must go through digital transformation in today’s economic environment. It’s all about moving faster and being more agile, which is more crucial than ever. The most recent drivers of progress in this domain are advances in generative AI (GenAI). Enterprises may experiment with new processes and move beyond traditional problem-solving using GenAI, which provides a great opportunity to accelerate value generation. It enables firms to swiftly test ideas, modify procedures, and uncover new solutions, allowing for continuous development, increased efficiency, and the creation of distinct value offerings with fewer resources.
However, AI or GenAI cannot be the exclusive driver of digital business change. Strategy, product, engineering, experience, and data, as well as AI, are the five critical competencies that must be blended. Only by implementing this all-encompassing plan will businesses be able to maximize the growth from their organization’s transformation.
What are the hurdles that new digital transformation technologies face? What benefits might AI offer in this regard?
People who are accustomed to utilizing these older methods will be opposed, as will legacy systems that have not been optimized to interface readily with new technology. The expense of implementing new technology is a big impediment for many organizations, particularly small ones. Another challenge posed by new technologies is a lack of experience in implementing and managing major change.
Despite its challenges, AI is a desirable investment for firms trying to monetize their data assets and use them for operational optimisation and competitive advantage. By intelligently automating boring activities, it allows people to focus on more sophisticated and strategic work. It offers personalized consumer experiences as well as insightful behavioral data.
Furthermore, with the most recent advancements in GenAI, it is possible to upskill current employees. by behaving as adaptive generalists, there is a need for expert employment.
How can businesses successfully address and eradicate AI prejudice in order to ensure justice and ethical use of AI systems?
When corporations embrace AI as a revolutionary tool, four critical factors must be prioritized: bias, ethics, governance, and legislation. Bias must be handled by recognizing unfair tendencies in data and algorithms and minimizing them through preprocessing and a variety of opinions. Ethics can be instilled by establishing clear norms for fairness, openness, accountability, and privacy. AI management will include monitoring inputs, outputs, and utilization.
Businesses may play an important role in safeguarding social interests while successfully resolving AI-related issues by integrating ethics and established standards.
Artificial Intelligence (AI) has steadily moved from the realms of science fiction and academia to the heart of various industries in this age of rapid technological advancement. AI is no longer a niche technology in 2023; it is a catalyst for innovation, growth, and sustainability across all industries. As a result, it is becoming increasingly important for every engineer, regardless of profession, to gain some level of AI competence.
AI has secured its place in modern technologies, whether through automation, predictive analytics, or decision-making algorithms. AI is altering the way we operate, optimize, and create, with applications spanning sectors such as healthcare, energy, transportation, and telecommunications.
This change means that AI is no longer limited to computer scientists or data analysts. AI is used by civil engineers to build, develop, and optimize infrastructure. AI algorithms are used by electrical engineers for energy management and defect identification. AI is used by mechanical engineers for predictive maintenance and quality control. The distinction between AI and other engineering disciplines has faded, prompting the development of a new set of abilities for engineers in the twenty-first century.
The need for engineers to have some AI experience goes beyond simply understanding the fundamentals of machine learning or data analysis. It is about becoming competent in the Fourth Industrial Revolution era, in which the physical, digital, and biological worlds are blending.
For real-time decision making in autonomous drones, aerospace engineers, for example, may need to collaborate with AI systems. To better manage and save resources, environmental engineers may need to use AI-powered predictive modeling. Chemical engineers may be charged with developing AI-enabled procedures to maximize production efficiency. As a result, engineers lacking AI skills will find it increasingly difficult to flourish in their respective domains.
Furthermore, AI tools and approaches have become critical in engineering for problem-solving, innovation, and design. Engineers must grasp AI principles, create AI models, and apply AI solutions to improve system performance, product quality, and service delivery.
Recognizing this demand, several universities and technical institutions are introducing artificial intelligence (AI) courses into their engineering curricula. These colleges are training future engineers for the shifting technological landscape by adding AI knowledge and abilities to their degrees. Furthermore, online platforms and Massive Open Online Courses (MOOCs) provide engineers with a flexible option to learn AI and stay ahead of the curve.
It is important not to disregard the ethical concerns of AI while considering AI competence. Engineers must comprehend not only how to create and use AI, but also the potential consequences of their work. As a result, problems like algorithmic bias, data privacy, and transparency should be included in AI education for engineers. This ethical literacy will ensure that artificial intelligence is used properly and fairly, preventing potential misuse or abuse.
Incorporation of Artificial Intelligence
The incorporation of artificial intelligence (AI) in numerous areas has revolutionized the discipline of engineering, changing the skillset required of engineers. As we go deeper towards the AI-driven world, engineers’ proficiency in their specific subject is no longer sufficient. They must comprehend, implement, and navigate AI technologies. Engineers may ensure they are prepared for the opportunities and problems that will arise in the age of intelligent machines by acquiring AI knowledge.
In the 1950s, every workplace had a specialized staff for switchboards. AI will do the same and open up new opportunities in the same manner that this occupation altered and made room for better alternatives. A quick internet search today indicates that timely engineering was not a skill a year ago. However, for the time being, the emphasis will be on upskilling, which is not a fresh concept for technologists.
Similar to the cloud, every engineer will be expected to understand artificial intelligence, including data analysis, AI system management, AI programming, and the use of AI models and libraries. Organizations are now debating the role of a chief AI ethical officer.
We used artificial intelligence to create customised chatbot solutions for finance in order to increase client relations and operational efficiency. Using GenAI, we created powerful intelligent chat interfaces for retail that automate merchandising while improving user interaction and product descriptions. Our customers use our AI-powered predictive analytics solutions to make data-driven decisions that improve the efficiency of their supply chains. We just unveiled PSChat, an internal generative artificial intelligence tool that leverages cutting-edge models to satisfy Publicis Sapient’s particular requirements.