Nik McDonald, Senior Account Director at Fujitsu, says absolutely not but that it does come with some risks and drawbacks that organisations should be aware of.

What makes AI such a hot topic across the industry right now?

Operators and suppliers have come to understand that artificial intelligence can have a seismic impact on their businesses, whether that be streamlining internal processes or improving the solutions, tools, services and experiences they provide to their customers. But as the understanding of AI has deepened, so too has the awareness that the impact AI has can be both positive and negative. This has ultimately left some organisations nervous and unsure how to approach it, let alone integrate it into their workflows, services and products. And this is why it’s become a hot topic, with stakeholders across the sector keen to learn more about it.

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Is there a certain type of AI that’s best suited to this industry? If so, what makes this type of AI such a good fit?

There are several types of AI including Narrow AI, General AI, Super AI, Reactive Machines, Limited Memory, Theory of Mind and Self Aware. The category most are interested in is Narrow AI and in particular, Generative AI – this is AI that can create new data including texts, images and videos by learning the structure and patterns of its training data to generate new ideas with similar characteristics. It can be trained to understand human language, programming language, art, chemistry, biology, law and countless other complex subjects and is often powered by Large AI models, often referred to as foundation models. This means Generative AI can perform a wide range of tasks including summarisation, classification and answering queries. This scope is what makes it ideally suited to businesses in this industry, regardless of whether they have a B2B or B2C focus.

Can you give a real-world example of Generative AI?

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ChatGPT is the most famous example. It’s essentially a chatbot that runs on the foundation of large language models, trained on vast amounts of data to produce texts that humans understand. Users ask a question and ChatGPT breaks down the query into smaller components to analyse their meaning and determine what the user is really asking it to do. It then returns the words and sentences it thinks best answer the query based on the data it’s been trained on. It’s pretty cool, but it does have some drawbacks and risks to be aware of.

Could you explain some of these drawbacks and risks?

The accuracy of results is a big concern, as is inconsistent outputs, bias, lack of explainability and even threats to privacy, security and intellectual property. People often forget that ChatGPT is a public service and that as well as sharing information, it consumes it. This means users must approach with caution if using it in the workplace or to ask questions about proprietary and sensitive information and data. Users also need to cross-check the answers that are provided to their queries given the inaccuracies and biases it can have.

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Does this mean Generative AI should be feared?

Not at all. Organisations should embrace the power of Generative AI and the clear benefits it can bring to their operations. We are already seeing companies use it, whether that be a slot studio harnessing its creativity to come up with new game concepts, designs, animations and even mechanics, to compliance platforms that use it to spot patterns in player behaviour. This sector has always been at the cutting edge, and I would include operators and suppliers to push the boundaries of AI but just to be mindful of some of the risks it presents.

How has Fujitsu approached Generative AI?

We have been busy developing a chatbot that’s similar to ChatGPT but that organisations can use with confidence. Instead of using publicly available data, it sits on top of the company’s data warehouse and allows teams and employees to ask questions and queries and have answers generated based on the proprietary data the foundation models have been fed on. Data can be siloed within the warehouse and with different levels of permission granted to different employees and teams. With our PrivateGPT, companies can really benefit from the power of Generative AI but with confidence that data is safe, secure and private, that responses are accurate and unbiased, and that the right level of permission is granted to individual employees.

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Can you give an example of how organisations can use your PrivateGPT?

Our PrivateGPT has lots of use cases including being able to ask any question, chat with company data, find new answers and insights, foster deeper collaboration, jointly generate insight and evaluate results and develop decision support systems. Specifically, it might be a legal and compliance team wanting to ask a question about a previous market entry and a specific legal requirement, or it might even be to offer a consumer-facing tool where bettors can see how a team or player had performed across historic bet outcomes. This is what makes Generative AI so exciting and why it will continue to be a hot topic for some time to come.

Without a doubt, 2023 has proven to be the year for artificial intelligence (AI), and the upcoming year, 2024, is expected to follow suit.

According to Forrester’s data, 2024 is set to be another significant year for AI, bringing about what we can call “intentional AI.” This means AI is moving away from mere experimentation and gimmicks, focusing instead on purposeful applications. Evidence of this shift is apparent in Forrester’s July 2023 AI Pulse Survey, which shows that 67% of businesses are actively incorporating genAI (AI technology) into their broader AI strategies.

In summary, 2023 has laid the foundation for AI’s continued growth, and 2024 promises to be a year where AI becomes more purposeful and integral to businesses.

Let me now share the five trends that we at InclusionCloud predict will dominate the AI landscape in 2024 and beyond.

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Trend 1: AI Changing Jobs Forever

Is AI ready to take over all human jobs? It’s a widespread concern, but let’s check whether there’s any truth behind it. While AI undoubtedly excels in certain areas, it falls short of matching human creativity and nuanced thinking in others. This distinction becomes evident when we dissect AI systems into two categories: open and closed. Open systems, characterized by external variables that remain beyond the machine’s control, are prone to unpredictability. For example,autonomous cars where another driver could unexpectedly cross a red light. On the contrary, closed AI systems, operating within controlled environments, exhibit remarkable efficiency, as seen in AI-powered chess software where the machine knows all potential moves.

However, within this context of AI’s transformative potential, real-world collaborations between humans and AI underscore a different narrative. In healthcare, AI-powered diagnostics equip doctors with faster and more accurate insights, ultimately improving patient care. Similarly, the manufacturing sector showcases seamless collaboration between AI-powered robots and human workers, resulting in heightened productivity and superior quality control. As I often emphasize, this collaborative approach shows that AI’s role is not in displacing jobs but in enriching them.

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Trend 2: Who Is in Charge? The Year of AI Laws

The rapid proliferation of AI has inevitably captured the attention of governments worldwide. Striking a delicate balance between fostering AI innovation and safeguarding public interests is the central challenge. In 2024, laws and regulations will be indispensable for deciding the worldwide trajectory of AI.

We’re now finding ourselves at an intersection where robust AI regulations aren’t just a choice, but actually imperative if we are to continue to move forward. It’s about ensuring responsible AI deployment without stifling innovation. Various industries, including the autonomous vehicle sector, grapple with complex regulatory questions. The adoption of AI ethics frameworks, as exemplified by initiatives such as the European Union’s, will delineate the boundaries of responsible AI implementation.

Trend 3: The Growing Impact of AI on Creative Work

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The amalgamation of AI and human creativity ushers in an exciting new era of innovation. AI-generated “hallucinations” are not mere glitches but powerful catalysts that inspire fresh perspectives and serve as creative brainstorming tools. However, as we navigate this creative frontier, ethical considerations take center stage.

In the entertainment industry, AI algorithms meticulously analyze viewer preferences to offer highly personalized content recommendations, enhancing the user experience. In design and art, AI collaborates with human creatives, suggesting novel ideas and even autonomously producing art. I believe that AI amplifies human creativity, but it is vital to establish ethical guidelines to navigate this exciting yet delicate collaboration.

Trend 4: AI Models Learning from Synthetic Data

The effectiveness of AI models is determined on the quality and quantity of training data available. This brings us to the debated subject of synthetic data, which has the potential to replace real-world data in a wide range of industries. For instance, in the insurance sector, synthetic data has emerged as a valuable tool for simulating complex risk scenarios, enabling insurance companies to refine their risk assessment models and streamline underwriting processes.

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We see synthetic data as a means to democratize AI development, making it accessible across various sectors. However, ensuring its reliability through strict testing and validation is key.

Trend 5: Supercomputers for Super AI

AI’s continual development and sophistication needs unparalleled processing power. As AI models get increasingly complex, cutting-edge hardware developments become critical. From banking to scientific research, industries largely reliant on AI are spending considerably in infrastructure capabilities to support these emerging models.

Supercomputers are the backbone of AI’s future, enabling the training of massive models and unlocking new frontiers of possibility. Quantum computing, in particular, has the ability to tackle complicated problems at unprecedented rates. According to IBM, this innovative technique has the potential to transform sectors such as medicine research and climate modeling.

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Conclusion

As we venture into 2024, the AI landscape promises a captivating narrative of change and innovation. These five trends encapsulate the profound impact of AI on our lives and industries. It’s a future where AI serves as an enhancement rather than a replacement, a future where navigating evolving regulations, fostering creative collaboration, exploring the potential of synthetic data, and investing in cutting-edge infrastructure are the guiding principles.

As the CRO of Inclusion Cloud, Nick Baca-Storni leverages his extensive industry experience to spearhead digital transformation initiatives, building strategic partnerships with tech giants such as Google, Salesforce, AWS, Oracle, and ServiceNow.

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