The below article is authored by RV Raghu, ISACA India Ambassador; Director, Versatilist Consulting India Pvt Ltd.
For generations, humans were at the top of the food chain, at least intellectually. However, over the last few years, human intellectual supremacy has been challenged by artificial intelligence (AI).
Artificial intelligence is set to go the way of software, which has generally taken over the world, and to go from ‘AI’ to ‘ai’ as it increasingly becomes integrated and embedded in all technology used by humans. This is going to be transformative like never before and businesses that leverage AI in this new digital era stand to gain tremendously.
While use cases abound, we are still just looking at the tip of the proverbial iceberg and this widespread adoption is not without its perils. Businesses will need to keep a hawk’s eye to ensure the downsides do not overwhelm the promised upsides.
Here are eight things businesses should do to safely and effectively leverage the transformative power of AI.
Understand risks – due to the nature and design of AI systems, inherent risks exist. This could be due to the training data or the model itself, not to mention the risks from the integration of AI into the existing technical landscape of the business.
Focus on governance – AI governance is key and must take the same priority as IT governance within the enterprise. AI comes with the potential to cause uncontrolled damage, impacting all stakeholders. Governance over AI ensures that its outcomes are aligned with business outcomes. Businesses will need to focus on aspects such as audits and effective testing of AI to ensure value is delivered.
Build skills – In Generative AI 2023: An ISACA Pulse Poll, more than half (52 percent) of the respondents said that no AI training at all is provided at their organizations, even to teams directly impacted by AI. Starting with the board of directors to front-line staff, training is required so that skills are developed, risks are understood, and desired benefits are delivered.
Prepare for incidents – This may seem counterintuitive, but at least in the foreseeable future, the potential for an increasing number of cybersecurity and operational incidents exists and preparation is key. Especially when it comes to operational incidents, being able to handle snafus quickly is critical to minimizing the blast radius and limiting damage.
Foster compliance – Laws governing AI and related technology are still evolving. New laws, especially those with a regional focus, are in the offing and businesses will have to be nimble enough to ensure compliance with these laws as and when they are promulgated.
Monitor the AI supply chain – AI is poised to become commoditized, which means the core AI/ML model may be owned and operated by a few entities with everyone else building products and services around these core systems. This essentially means that businesses are prone to mistake the simplicity of the interface/integration as a proxy to the solution itself, which is not the case. AI/ML systems comprise disparate components such as the algorithm, data, the training, etc., which may be made available by multiple entities that are essentially a black box. Businesses will need to build proxy controls over the various elements in the AI supply chain to minimize and manage risk.
Manage data – As cliched as it sounds, data is going to fuel the AI juggernaut. Of course, this is not just the data that was sourced from the internet and used to train the model, but data from the business and its customers. Data-related challenges abound on the input and output side. On the input side, unless data is managed, it can reflect the same biases and flaws of the real world. On the output side, decisions need to be explainable and co-relatable to the data that was fed in. Data-related challenges need to be grappled with proactively.
Approach holistically – There are many moving parts at the intersection of AI and the business. To succeed, businesses will need a holistic approach, one that helps tie all the loose ends together which usually calls for a framework, a method to the madness if you will. ISACA’s Digital Trust Ecosystem Framework (DTEF) is tailor made just for the digital era and businesses will benefit from a unified view the framework provides across the factors of quality, availability, security and privacy, ethics and integrity, transparency and honesty and resiliency that consumers believe are factors that help determine trust. Building and fostering digital trust is going to be key to successfully unleashing the transformative power of AI.
A holistic approach to integrating AI into the business starting with an understanding of risk and establishing governance practices is going to be key for businesses to survive and thrive in the age of AI while also delivering value to all stakeholders.
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