5 questions to...
Igor Bailo
Interview to the Executive Director Data & Analytics of Engineering.
Igor Bailo from 2023 is Executive Director of the Technology Business Line (TBL) of Data & Analytics, within the Digital Technologies business unit of the Engineering Group.
The Data & Analytics TBL brings together Engineering's expertise in the areas of data management, business intelligence, advanced analytics and artificial intelligence, counting about 380 professionals and more than 50 projects carried out each year. Data & Analytics also includes a Research and Innovation Lab with about 100 professionals and more than 20 partnerships and academic collaborations.
Previously, Igor was Executive Board Member and Group Chief Operating Officer at WIIT and has held roles of increasing responsibility in the world of IT and Financial Institutions, after a career start at McKinsey & Company.
In addition, he is a university lecturer in Project Management at the Catholic University of the Sacred Heart in Milan.
1. HOW IS THE APPROACH TO AI EVOLVING TO TURN THIS TECHNOLOGY INTO A REAL DRIVER OF PROGRESS AND INCLUSION, AND WHAT ARE THE BIGGEST CHALLENGES IN THIS JOURNEY?
From a technical point of view, along with the development of Private Generative AI we are witnessing a shift from the closed source approach to foundational models to an open-source approach.
As far as language models are concerned, the increasing use of Small Language Models is enabling increased efficiency, cost-effectiveness and speed of many Gen AI applications. One example is the real-time use of language models through voice, where the system interacts with humans smoothly and naturally, even when interrupted, just as would happen in the context of a conversation with a human being.
But alongside technological evolution, the other very important area of development is related to the reliability and diffusion of AI. Indeed, AI-based applications are revolutionizing the way we work and live, and their pervasiveness is accompanied by challenging issues such as equity, transparency, accountability, reliability, and security of AI solutions.
A Responsible AI approach involves taking specific attentions from the collection and management of raw data, in the writing of algorithms and their training, to the very use of the information received by AI-based systems. Promoting and supporting inclusion and diversity during AI development ensures that the solutions created meet the needs of a variety of stakeholders and that the benefits brought are distributed equitably.
Generative AI applications can also enable principles such as usability, facilitating accessibility to services in a simple, intuitive, and equitable manner, regardless of education level, experience, and ability, by combining different types of communication.
2. FROM DATA ARCHITECTURE TO ADVANCED ANALYTICS: HOW DOES A HOLISTIC APPROACH ENABLE THE MANAGEMENT OF THE ENTIRE DATA CHAIN TO TURN IT INTO A REAL COMPETITIVE ADVANTAGE?
Customers start with an articulated and diverse information systems endowment that reflects the complexity in which they must operate. In Engineering, we support customers with multidisciplinary teams that take a holistic end-end approach, starting with Data Architecture and Data Management, and ending with the development of Artificial Intelligence and Advanced Analytics solutions that enable the creation of additional value and the achievement of the best response to the specific business need.
As part of our strategy, adopting a composable approach allows us to nimbly assemble, for example, AI and Machine Learning modules to create new solutions, responding precisely and flexibly to changing market needs and developing tailored solutions to enable customers to gain a real competitive advantage.
With respect precisely to the adoption of AI solutions, many customers have the specific need to have full control over available data, intellectual property, protection of sensitive data and patents: this is the case, for example, of customers operating in the finance and healthcare markets, PA, and all companies that tie their revenues to creative invention.
In these cases, we resort to so-called Private Generative AI, which enables the development of AI solutions in a private environment, ensuring full control over data and access to it.
3. WHAT POSITIVE IMPACTS ARE PRODUCING THE DEMOCRATIZATION AND SIMPLIFICATION OF ACCESS TO DATA AND INFORMATION, ENABLED BY THE COMBINATION OF AI AND BI?
By combining elements of Business Intelligence and Advanced Analytics & AI, it is possible to support the entire value chain from descriptive to predictive and prescriptive aspects, leveraging the full variety and breadth of available sources. Through “self-service,” that is, the ability of users to access and analyze data autonomously and immediately, the access to valuable information can be democratized and simplified.
In the world of customer support and customer care, using natural language processing skills, we have built several AI solutions that can interact with customers similarly to human interaction.
These Virtual Assistants understand the content of conversations, identify intentions and classify requests based on industry-specific information. The benefits are: increased quality of conversations and problem-solving capabilities, reduced burden on human staff, improved customer service sentiment scores and 24/7 support availability.
Another interesting application of virtual assistants based on generative AI is in business decision-making support. In this case, the need for spreadsheets, reports or dashboards is eliminated: it is possible to directly request the necessary information in natural language and receive a relevant and comprehensible response, based on a wide range of data from different available databases.
With this solution, reporting production time is significantly improved, enabling faster and more effective business decisions and the implementation of corrective action to anticipate or avoid a critical event.
4. HOW IS GENERATIVE AI IMPACTING THE DIGITAL TRANSFORMATION JOURNEY OF COMPANIES AND WHICH USAGE SCENARIOS PRESENT THE MOST PROMISING FUTURE DEVELOPMENTS?
From managing hidden processes to customer interactions, Generative AI is having a profound impact, enhancing the capabilities of both individuals and organizations.
In the world of enterprise applications, we are seeing increasing integration of Generative AI into enterprise solutions: in learning systems, training, user support, simulations, testing, design, and coding. This integration will increasingly facilitate the adoption of AI to organizations of all sizes.
Among the most interesting applications of generative AI are certainly those in the world of Healthcare, where AI enables significant benefits to be generated across a very wide range of citizens. For example, Engineering is developing a project that converges the needs of diagnostics with the opportunities offered by advanced AI tools that support anatomo-pathologists in the automatic identification of important pathologies (such as colon cancer) from the image of the cells of a sample in a slide.
Other interesting areas of application of Generative AI are the Energy&Utilities world, where it is possible to develop intelligent management systems for complex facilities (combining generative and non-generative AI), as well as the aforementioned retail sector with the implementation of virtual assistants.
5. HOW DOES RESEARCH ACTIVITY AND PUBLIC-PRIVATE COLLABORATION, INCLUDING IN THE SUPRA-NATIONAL SPHERE, ALLOW TO GOVERN THE RAPID EVOLUTION OF NEW TECHNOLOGIES AND THEIR PERVASIVENESS IN DAILY LIFE, PARTICULARLY WITH REGARD TO ISSUES RELATED TO RELIABILITY, ETHICS, AND COMPLIANCE WITH LAWS PROTECTING THE INDIVIDUAL?
Since years Eng is involved in several European and national institutional tables to understand how to direct the evolution and adoption of Generative AI in Italy in an ethical and socially sustainable way.
We are convinced that the ethical approach should not only be managed at the normative level, but concretely demonstrated through initiatives and projects that operationally show its use of AI for social good. In this direction, for more than a decade we have been experimenting with the use of AI to improve digital accessibility for people with disabilities, for energy sustainability, and to counter climate change and misinformation.
Our in-house R&I Laboratory, supports the Group in the research and development of new methodologies, algorithms and technologies for data-driven ecosystems and AI. Through an interdisciplinary and innovative approach, in the context of national and European programs, it carries out ambitious and high-impact projects combining efficiency, security and accountability. With more than 60 research projects in data, analytics and AI, Engineering is one of the most active players in the European research landscape.
The results derived from the world of research are then capitalized in the solutions we implement for our customers using precisely the Responsible AI approach and the advantages offered by Private Generative AI described above.
AI-based applications are revolutionizing the way we work and live, and their pervasiveness comes with challenging issues such as equity, transparency, accountability, reliability and security.
Igor Bailo
Executive Director Data & Analytics, Engineering
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