Artificial intelligence (AI) has become ubiquitous and has become a key topic of discussion among senior management and board members. Three out of four CEOs believe that organizations with the most advanced generative AI wins, according to a recent CEO study from IBM’s Institute for Business Value. Additionally, 43 percent of CEOs in the study report that their enterprises are currently using generative AI to inform strategic decisions.
In the Philippines, organizations have started exploring the capabilities of generative AI to reap its benefits.
PJ Lhuillier, the parent company of the Philippines’ leading and largest micro financial services provider Cebuana Lhuillier, is also driving AI adoption in its organization that includes 3,500 branches nationwide.
It is exploring generative AI to streamline and better address customer inquiries with an intelligent, consistent and conversational AI chat assistant across multiple digital channels like social media and its mobile application.
Generative AI gained its momentum in 2023 as businesses in various industries explored its potential. We see this continuing to soar in 2024 with more organizations developing use cases to address specific business challenges, while upholding trust and prioritizing data ethics and governance.
AI movements to look out for in 2024
Enterprises cannot afford to ignore the potential of generative AI. While there are concerns from businesses about the risks of AI, such as hallucinations, bias, prompt hacking, copyright infringement, trust that there is AI technology available today, such as watsonx from IBM, that enables you to mitigate such risks.
There is no doubt AI is here to stay and organizations risk getting left behind if they don’t start adopting. Learning more about this technology must be a central focus in the upcoming year. As organizations learn to embrace the capabilities of generative AI, they must also safeguard against potential harms by embedding governance and safety into the core of their strategy.
Here are three AI trends shaping 2024:
Organizations in 2024 can benefit from the emergence of small language models (SLMs) and pretrained models, which will be easier and cheaper to deploy. Unlike large language models (LLMs) which are trained on trillion parameters and require costly computation resources for training, small language models have fewer parameters and are typically trained for specific tasks. They are more efficient and cost less to train.
Pretrained models like IBM’s Granite are developed and trained on datasets that have been carefully curated to mitigate unwanted bias and objectionable content. Businesses can start using them by adding their own data to the pre-trained datasets to undertake specific tasks from code generation to improving workflow automation in a safe and secure manner.
In the new year, AI governance emerges as the top priority. More than half of the 3000 global and Association of Southeast Asian Nations (Asean) CEOs surveyed by IBM also revealed their concerns about data security while about 48 percent worry about bias or data accuracy. Organizations, thus, must commit to protecting data and intellectual property, supported by tools to mitigate risks.
Establishing trust in the generative AI applications starts with having fair, holistic and unbiased datasets. Regular monitoring and model retraining to adjust for changes in behavior are essential to ensure fair decisions and responses.
IBM embraces five foundational pillars of trustworthy AI: Explainability, Fairness, Robustness, Transparency and Privacy, which underpin the development, deployment and use of AI systems.
Guided by these principles, IBM Research has made its Trustworthy AI toolkits publicly available for use by developers and data scientists, which include AI FactSheets 360. Similar to nutrition labels for food, this toolkit increases transparency so that AI consumers better understand how the AI model or service was created.
Governments will continuously take proactive measures by enacting regulatory frameworks to address risks and safety concerns, as well as helping improve the preparedness of industries and society to mitigate these risks.
The Department of Science and Technology – Advanced Science and Technology Institute has recently shared its various AI-driven initiatives including AI4Mapping and AI for agriculture, an Internet of Things and AI-based plant phenotyping, a natural language interface for relational databases, and an AI model hub aimed at democratizing access to optimized AI models.
Meanwhile, Asean recently released its guide on AI Governance and Ethics, which includes recommendations that governments in the region can consider implementing to design, develop, and deploy AI systems responsibly.
With the upcoming regulations, it is imperative for organizations to adopt AI responsibly. They must choose a capable partner that would help them manage their AI responsibly at enterprise scale.
2023 was the year people paid more attention to the possible impacts of generative AI across industries.
The lesson for businesses in 2024 is clear: don’t wait, get your feet wet, try, learn, build and deploy, but ensure to do it responsibly. INQ
The author is country general manager and technology leader of IBM Philippines