Wipro Chairman Rishad Premji noted that IT service providers can utilize their deep knowledge of clients' business processes, systems, and operational environments to achieve efficiency, implement innovations, and drive AI-based growth.
Wipro Chairman Rishad Premji noted that IT service providers can utilize their deep knowledge of clients' business processes, systems, and operational environments to achieve efficiency, implement innovations, and drive AI-based growth.
Thanks to years of experience understanding customer workflows, IT service companies are well-positioned to transform and organize their systems using AI and extract value from them. However, these companies have faced difficulties due to prolonged weak demand and an unstable geopolitical situation, leading to annual growth of less than 5 percent over the last three years, a trend that may persist this year.
Furthermore, AI is reducing the revenue of traditional players as they have to pass on savings to clients. Nevertheless, Premji emphasized that AI will not only increase efficiency but also open up new opportunities for growth and innovation, as enterprises seek to move beyond pilot projects and integrate AI into their workflows, increasing demand for data and AI-based IT modernization.
During Wipro's 80th annual general meeting on Wednesday, Premji stated that 'new sources of growth will emerge. Organizations must rethink processes and workflows, enterprise architecture, and data modernization. This transformation journey will be carried out gradually, through the joint work of new operating models, people, and AI.' As an example, he cited that Wipro's internal financial closing cycle was reduced from 24 to eight hours by using AI.
An S&P Global Ratings report published earlier this week warned that over the next three years, Indian IT service providers will face increased competition from AI-native firms, which could undermine their revenue base if they fail to remain competitive and protect their core business. Premji added that last year, the industry was cautious due to persistently weak demand and geopolitical volatility. Clients continued to focus on cost optimization deals, even investing in AI to transform their talent and platforms.
He also noted that cost optimization deals, although large, require significant time to implement after signing and put pressure on operating margins as traditional players compete for the same market share. In contrast, smaller, AI-focused deals generate revenue faster, provide a regular stream of income, and have higher margins.
CEO and Managing Director Srinivas Pallia clarified that enterprise AI goes beyond just large language models. It includes understanding existing limitations, process mechanics, integrating domain expertise, ensuring data security, and managing change. Moreover, AI is driving the shift towards new commercial models—from effort-based pricing to consumption, transaction, and business outcome-based models.
Access to generative artificial intelligence has lowered the barrier for conducting experiments, but this does not eliminate the engineering requirements necessary to implement systems in production. While demonstrating AI capabilities has become surprisingly easy, its effective deployment remains a significantly more complex task.
Today, a convincing prototype can be assembled in a matter of hours or days. However, the real work begins when an organization expects the system to operate with confidential data, integrate with existing platforms, comply with regulations, serve customers, and deliver measurable returns.
The author notes that this is the most significant change he has observed in conversations with African enterprises over the past two years. Leaders are now spending less time contemplating what AI can do and more time identifying areas where it can reduce fraud, improve customer service, accelerate software development, process documents, or remove bottlenecks in costly workflows.
This shift from curiosity to commercial evaluation strengthens confidence in AI's potential in Africa. A production system must possess reliable data, secure access, clear accountability, integration with core platforms, and a mechanism for monitoring performance over time. It must know when to make a decision, when to pause, and when to hand the decision over to a human.
These requirements are particularly critical in sectors such as banking, insurance, healthcare, and telecommunications, where an erroneous response is still possible. Demonstration only proves the technical feasibility of an idea; deployment in production must demonstrate the ability to create value without introducing unacceptable operational, safety, or regulatory risks. This standard will be how investment in enterprise AI is judged in the future.
Sometimes Africa is characterized as having an AI advantage due to fewer legacy technologies compared to developed markets. However, this is only partially true. Many African organizations manage complex technological stacks built over decades, while a significant part of the continent faces uneven connectivity, limited computational power, and a shortage of specialized skills.
A stronger advantage lies in how African markets innovate under constraints. Businesses here are accustomed to serving mobile-device-oriented customers amid fragmented infrastructure, multiple languages, and widely varying levels of access. These conditions stimulate practical innovation, as technology must solve an obvious problem before it receives large-scale funding.
This creates space for AI systems tailored to the realities of Africa. Local datasets, languages, regulations, and consumer behavior cannot be viewed as a localization layer added at the end. They influence whether the system understands the context in which it is supposed to function.
The expansion of local cloud infrastructure has strengthened the foundation for this next stage. Microsoft Azure opened its South African cloud regions in 2019, AWS launched the Cape Town region in Africa in 2020, and Google Cloud opened its Johannesburg region in January 2024. These investments provide organizations with more options when considering latency, fault tolerance, data residency, and regulated workloads. They also facilitate the creation of modern data platforms capable of supporting AI at an enterprise scale.
Local infrastructure alone does not create sovereign AI. The author defines sovereignty as meaningful control over the data, access, governance, auditability, and systems that the AI model can affect. Africa must continue to utilize global cloud platforms and leading foundational models while developing the local data, skills, and industry expertise necessary for their responsible application.
The financial sector already demonstrates some of the clearest use cases, as the economic viability is evident. Fraud detection, risk assessment, intelligent document analysis, customer service automation, and regulatory reporting can be linked to specific costs, service outcomes, or reduced risk exposure.
The same principle will drive adoption in other areas. AI will gain traction when it becomes part of the existing operating system, eliminating work from the process rather than adding a new interface that employees must learn. Agentic AI will expand this by coordinating tasks across workflows, although its value will depend on the quality of the data, rules, and oversight surrounding it.
For business leaders, the next decision should start with the outcome the organization aims to improve, the available data to support it, and the level of autonomy that can be justified. Model selection should be postponed until the workflow scenario is clear. The future of AI in Africa will be shaped by organizations capable of turning promising ideas into robust systems that serve customers, manage risks, and increase the efficiency of work execution.
The Johnson Space Center in Houston has begun recruiting participants for the Moon & Mars Exploration Analog (MMEA) ground expedition. This unique program, scheduled to start no earlier than August 2027, involves the complete isolation of a group of four to six test subjects from the outside world for an entire year.
The main goal of the expedition is to provide scientists with the opportunity to prepare for future real missions to the Moon and Mars. Organizers are looking for US citizens or individuals with a Green Card who meet specific criteria: age between 30 and 55, height no more than 188 centimeters, and physical and psychological endurance.
Candidates must have a higher education in exact sciences, engineering, or mathematics and possess significant work experience. The selection process includes a thorough medical commission and in-depth psychological testing.
For the entire year, volunteers will be housed in the closed Pavilion 220 in Texas. Here, scientists have recreated three interconnected spaces to model different phases of space travel. Initially, the crew will reside in a two-story cylindrical spacecraft approximately 63 square meters in area, simulating a long journey.
Upon arrival at the simulated planet, participants will move into a spacious single-story Martian habitat, which covers about 158 square meters and was created using a 3D printer. This house is equipped with living quarters, a kitchen, a laboratory, and a sand area for conducting both virtual and physical surface excursions.
A compact rover designed for two people is provided for more detailed research. In this limited cabin, equipped with sleeping berths and a portable toilet, participants will spend several days in complete autonomy, allowing an assessment of their ability to cope with extreme crowding and temporary team separation.
Life in the complex will be strictly regulated according to a military schedule, similar to the routine of the International Space Station (ISS): eight hours of sleep, clearly defined working hours, physical exercise, and life support system maintenance. Furthermore, participants will be in a complete information vacuum, excluding access to the internet, social media, television, and regular phone calls.
The only ways to communicate with Earth will be through text news briefs and rare video calls with loved ones and psychological specialists. A delay of several minutes will be used to increase the realism of communication with Mission Control. During the simulation of passing the ship behind the Sun, the crew will face a complete two-week silence.
The volunteers' diet will consist exclusively of dry space rations, while fresh vitamins will be obtained from greenery grown in a small hydroponic farm. These 14 months of strict limitations and constant medical examinations will allow NASA to study aspects such as psychological exhaustion, group cohesion, and bodily function under stress, ensuring the safety of future space missions.
Additionally, it should be noted that NASA previously allocated about $600 million to three private companies to prepare for the creation of a Lunar base. The task of these companies is to deliver necessary equipment to the Moon using unmanned vehicles.
Researchers have discovered a significant diversity of genetic material preserved in the Turin Shroud, which many revere as the cloth that wrapped the body of Jesus Christ after the crucifixion.
The analysis showed the presence of DNA from dozens of plant and animal species, as well as genetic traces of at least 14 individuals of different origins, providing new insights into the biological history of this cloth. According to scientists, the amount of DNA extracted from the Turin Shroud was higher than expected even for a very frequently used blanket.
Among the identified traces were organisms such as carrots and tomatoes, as well as fish, dogs, and cats that came into contact with the fabric over centuries. The Turin Shroud continues to spark debate: it has been revered for centuries as a presumed burial shroud, but its authenticity remains a subject of discussion among believers and skeptics.
The exact origin of the cloth is unknown; the earliest recorded fact of its appearance dates back to 1354 in Liri (France). To better understand the object's history, researchers used organic residues collected from the surface of the fabric in 1978. These samples were re-examined using modern genetic analysis methods, which allowed for the identification of a wide spectrum of species that contacted the shroud.
The analysis revealed DNA from at least 14 individuals from different parts of the world. Researchers claim that one of the genetic profiles almost certainly belongs to a scientist who collected samples in the 1970s, described as being of European and Jewish descent. A rare genetic trait associated with the Aramaic Druze people living in the Middle East was also found. Another surprising result was the discovery that nearly 40% of all human DNA found originated from India. The most likely explanation for this is that the flax used to make the fabric was imported from the Indus Valley.
In addition to human DNA, the study revealed a great diversity of plant and animal genetic material. Among the cultivated plants identified were tomatoes, cucumbers, melons, potatoes, and pistachios. The authors of the study noted a strong presence of peanuts, belonging to the Fabaceae family. Traces of bananas, peppers, corn, and carrots were also found. Among the animals were dogs, cats, chickens, pigs, and cattle, as well as horses and rabbits. DNA from almonds and walnuts was also found in the analyzed samples.
The investigation also revealed unusual marine contaminants, including Atlantic cod and anchovy. Furthermore, red coral from the Mediterranean, which was used in Roman times for making jewelry and other symbolic items, was identified. Although researchers cannot determine how, when, or where each species contacted the Turin Shroud, some findings help establish a timeline for some of these contaminants. For example, the detected carrots belong to European varieties that were first cultivated between the 15th and 16th centuries. Moreover, many identified species originate from Latin America, and the authors suggest this occurred only after historical voyages that led to the arrival of Europeans in America in 1492.
Although the study does not answer questions about the age or authenticity of the relic, genetic analysis provides new information about its journey. Professor Naomi Procopio, one of the study's authors, stated in her statement: 'The Turin Shroud represents a rich archive of genetic information accumulated over centuries of human interaction and environmental impact.' She added that 'while DNA evidence cannot answer all questions about the age or authenticity of the cloth, it gives a new perspective on its biological history and demonstrates how forensic science advancements can reveal new information from historical artifacts.' The results were published in Scientific Reports.
