That past performance is not a guarantee of future results may be true in sports and banking, but when it comes to artificial intelligence (AI) and machine learning (ML), it is essential to understand the past in order to build the future.

2023 has been a great year for AI, especially generative AI, which is a niche, but a very exciting application of AI to synthesize “new” ideas or content. The potential to leverage technology to help with human-like conversations, summarize large amount of data and develop the next level of customer engagement has led to significant and appropriate attention by business executives. But will 2024 continue these trends?

Less Hallucinations, Delusions and More Decisions

Hallucination is the term given to misrepresentation or incorrect predictions provided by AI models due to various factors. Hallucination is a common experience due to the current maturity curve of technology and people in leveraging language models. As adoption of large language models (LLMs) becomes more prevalent next year, so will the occurrence of horror stories or delusions around incorrect use resulting in unintended consequences and bad PR for some enterprises. Some corporations will institute safeguards and look for more pragmatic and measured outcomes while focusing on tracking value based on decisions provided by AI versus just the novelty of using technology.

This is an important step towards leveraging technology at scale and will drive innovation around improving AI performance for business, resulting in transparent and explainable solutions.

Actionable, Equitable AI

The goal for leveraging AI by enterprises will continue to be on business decision automation as well as creating an equitable environment to foster productive collaboration and transformation. To that effect, AI codes of conduct will be incorporated and followed in most of the industry, placing emphasis on transparency, and actionable, measurable recommendations with well-understood known and unknown biases in the solutions.

The latter is more important in talent recruitment and management, but also in diverse fields like security and manufacturing processes. Look to environmental, social and governance (ESG) models leveraging AI to score new company initiatives and be tracked by some larger companies.

New Roles in the Industry

Heard of prompt engineer? Chief AI officer? New generations of skills and jobs will become commonplace and will compete for attention for the new generation. In some cases, the focus on arts and communications degrees to help build complex enterprise ecosystems could displace technical and engineering-focused jobs, since the focus will be on creating near-human customer experiences in distribution and e-commerce companies.

The use of AI to drive improved product manufacturing or inventory management could lead to a job revolution 2.0 in manufacturing where there will be aggressive investment in upskilling the existing workforce to leverage AI in decision making. The focus will shift towards augmented intelligence, a concept where AI is leveraged to assist business functions.

User Experience (UX) Becomes Augmented Intelligence Experience (AIX)

The resulting transformation could cause a paradigm shift in how business applications are designed and used. For those who are old enough to remember the blue screen AS400 screens and worked through the transformation of enterprise software to be UX driven (forms, controls and charts), and then context driven (CX) to reduce the need to have to hunt for information in aforementioned forms – there could be a new approach based on augmented intelligence experience (AIX).

The concept is that AI will provide access, via multiple avenues, to recommendations or options for human operators to perform business actions. The focus will be on “push” of decisions or choices, versus the current traditional “pull,” where users have to spend time on screens in multiple systems to perform work.

Composable Enterprise Systems

Think of our current business ecosystem where most enterprises have hybrid architecture with various cloud-based solutions loosely integrated with on-premises systems and Excel. A move to AI-based decision making will result in acceleration toward true composable enterprise systems. An architecture that can leverage data from various sources and systems (without duplication or replication), fed into different interchangeable enterprise planning systems could change the landscape of the SaaS industry.

I expect cloud application providers to market themselves as business or decision platforms and be measured by how quickly they can be integrated within organizations with minimum setup time. Enterprise software selection could become as painless as subscribing to your favorite media content provider.

Data Protection and Monetization

The push for open APIs and data-driven decision systems will push and promote more data protection and monetization strategies. There will be continued focus and acceleration, due to AI, on managing personal behavior information by consumers and perhaps a change in commercial models used by e-commerce sites.

While GDPR and similar requirements have pushed the concept of data protection to the forefront, I expect next year will continue to accelerate the trend, due to AI, for individual consumers to own and manage their data rights and even potentially have commercial models to allow them to monetize their e-behavior.

Self-Actualizing AI?

I am optimistic that the change driven by AI will result in greater wealth and quality of life for everyone in 2024. The quest to make AI more intelligent and intuitive will continue, but we won’t achieve self-actualizing AI any time soon.

AI investment will accelerate and drive other innovations, but the goal of omniscient AI, for those who would pursue it, will remain a distant dream.