Generative AI can improve corporate operations. IBM Consulting’s EMEA Leader for Data & Technology Transformation, Giorgio Danesi, discusses how businesses may ethically deploy generative AI.
AI adoption and its effects on businesses and society are tipping points worldwide. It’s used in virtual assistants and IT procedures. ChatGPT has also given consumers control over technology.
Foundation models, generative AI, and governance provide huge potential. AI is improving customer service, manufacturing, health, and aerospace. Many firms struggle to trust AI and ensure its responsibility.
Modeling AI
Despite fast breakthroughs, AI was difficult to scale and deploy until recently. Access to AI-related expertise has also limited the technology’s penetration to larger organizations, especially since each new application needed a new AI model.
McKinsey says 52% of digital resources go to AI, yet a recent IBM research revealed that few AI initiatives achieve the financial benefit shareholders anticipate.
ROI averages 5.9%, below the 10% cost of capital. Why? Because it’s not only about investing in AI, but also data availability, trust-based strategy, governance, skills, and culture. Balanced firms get a 30% greater ROI.
Foundation models—deep learning algorithms pre-trained with massive data sets—are used to build more complicated models. They tailor AI to your company’s data and subject knowledge. This is difficult and requires effort, but it amortizes the original AI model development work each time it is utilized, increasing ROI and speeding time to market.
Early customer work shows a 70% acceleration in time-to-value.
Automated value
AI and automation adoption is definitely becoming simpler, driving implementation. Thus, the worldwide generative AI market has risen to $11.3 billion and is expected to expand 35.6% by 2028.
Even though Europe has a skilled labor deficit, it’s easy to imagine that AI would threaten jobs. AI automates repetitive activities for all industries.
IBM research indicated that 30% of IT professionals said AI and automation solutions save staff time. From contextual and personalized email answers to code-generated technical documentation, this has many uses. Conversational AI assistants let ABN Amro service millions of clients.
If the talent gap went unchecked, lost income might soar. Companies invest in AI because it’s an investment in people.
AI ethics
Governance debates intensify with AI investment. No company wants to be accused of prejudice. Its reputational harm is costly and hard to repair.
Thus, all elements of a business must be protected from inadvertent bias, including AI workflows, which should be created with accountability, openness, and explainability from the start. This may be done by diversifying datasets, testing and evaluating models, and supervising them.
AI rules are evolving, and violation may result in audits, penalties, unfavorable news, and lost client trust. Global companies with operations in numerous countries must comply with many country-specific laws.
If that wasn’t confusing enough, highly regulated industries like healthcare, finance, and government services face additional challenges in meeting industry-specific regulations like the EU’s Digital Operational Resilience Act (DORA).
AI advantage sought
IBM has witnessed how AI, data, governance, and trust can improve business. IBM Consulting created 1,750 AI use cases for 1,250 clients in 2022.
However, obtaining such value needs a comprehensive grasp of the intricacies of the technology involved and a human-centered, principled approach to AI deployment.
Businesses should be AI-advantaged, not simply users. AI mission.
IBM Consulting built a generative AI center. The hub has helped over 100 customers maximize their AI advances since its founding.
