AI Implementation: Value for Business
- Is AI adoption a forced measure to maintain competitiveness or a strategic step into the future?
- How does your company perceive AI adoption?
- The economic impact that can already be observed
- AI threats to the company (human factor, control over information accuracy, cost of errors)
- Key competitive advantages/results of implementation
- Obstacles hindering progress
Experts participating in the plenary discussion on the relevance of AI implementation in business include:
- Professor Jean-Pierre Auffret, Ph.D., Co-founder and Vice President, International Academy of CIO
- Sudin Baraokar, AI Engineer, Digital Transformation Industry Expert, Global IT & Innovation Advisor/CIO
- Ravishankar Ramakrishnan, Vice President & Head of IT, Exela Technologies
- Chubak Temirov, Deputy CEO, High Technology Park Kyrgyzstan.
- Moderator: Oleg Aksenov, CTO & co-founder, Nomad Digital and Unlock.Auto.
The panel discussion delves into the necessity of AI adoption for businesses and the potential implications for competitiveness, innovation, and transformation.
Topics:
- Is AI adoption a forced measure to maintain competitiveness or a strategic step into the future?
- How does your company perceive AI adoption?
- The economic impact that can already be observed
- AI threats to the company (human factor, control over information accuracy, cost of errors)
- Key competitive advantages/results of implementation
- Obstacles hindering progress
Is AI adoption a forced measure to maintain competitiveness or a strategic step into the future?
The discussion begins with the assertion that every company will eventually be forced to adopt AI. AI adoption varies across industries, with some seeing it as imperative for staying competitive, while for others, it's less of an immediate need. Jean-Pierre Auffret drew parallels to the digital transformation era, highlighting the risks of falling behind without embracing AI and acknowledging the possibilities of failure and different paces of adoption. New technologies like MLOps, data pipelines, autonomic databases, and predictive analytics help to improve the overall governance risk and compliance and reduce fraud, especially in banks. Sudin Baraokar added, that sometimes – from his experience in the State Bank of India and Barclays Bank – there are >3,500 data sources to be captured so the companies just don’t have any other option than to use AI.
How does your company perceive AI adoption?
Speakers shared their experiences with AI adoption as a transformative tool, drawing from examples in government agencies and large financial institutions like the State Bank of India and Barclays Bank. Chubak Temirov said that the government of Kyrgyzstan recently financed the purchase of a 1 PetaFlops supercomputer to help 350+ resident companies of the High Technology Park. One of these companies was working on a speech recognition project in Kyrgyz, which is a relatively small language with only ~7 mln native speakers. Usage of the supercomputer allowed it to build more powerful natural language processing (NLP) models and a Named-Entity Recognition (NER) dataset, which was otherwise very hard to achieve given the limited capacity of people with the required competencies. Another project is dedicated to the creation of Akylai, a Kyrgyz-speaking AI assistant, similar to Apple’s Siri or Yandex’s Alisa. As its creators say, its main goal is to increase the usage of the Kyrgyz language in the digital world.
There are of course cases of strong resistance to AI. To avoid this, you need to involve the stakeholders from the planning stage, have a proper business case and enhance your value proposition, because AI will not be a one-size-fits-all solution. You need to find the areas where the organization faces processing challenges, a lack of data insights, or a bottleneck of repetitive tasks, and then propose solutions to each problem.