6 Predictions for 2024: Will Generative AI go mainstream in global content?

Is 2024 the year GenAI transitions from an emerging technology to a mainstream powerhouse?

 Recent trends provide a telling preview. In 2023, one-third of companies were using GenAI in at least one business function with predictions for meaningful changes in the workforce moving into 2024. This adoption is not just a fleeting trend but a harbinger of significant workforce transformation as we delve deeper into 2024.

There are most likely numerous board discussions and IT meetings underway to implement GenAI tools for company-wide use, a significant step towards making AI an indispensable daily companion and productivity-enhancing tool, particularly for content creation.

With more than 13 years of experience in the language and localization industry, it's evident that the rapid evolution of AI is driving a notable shift, even though the full extent of its impact remains uncertain.

 As we get into 2024, let's explore six areas where GenAI is set to make a lasting impact on global, multilingual content and the language industry:

 Content Development Moves Upstream

Retaining the Human Touch in AI-Driven Environments

Ongoing Analysis of MT vs LLM Performance

Deepening of AI Ethics and Governance Conversations

Advancement of Vendors in the AI Value Chain

Increase in AI-as-a-Service (AIaaS)

Let's look at each one in more detail…

 1) Content Development Moves Upstream

 LLM-enabled assistants in tools like Microsoft Office (Copilot), Hubspot, Canva, and WordPress will shift the multilingual content generation process and ultimately lead to a massive increase in content volume produced. This will impact the overall localization and translation process, as language variants will be produced from source, giving more emphasis on content validation of AI output i.e. accuracy, than actual translation. Other activities such as automatic transcription and AI-generated summaries will also provide a more efficient workflow for content.

 Furthermore, using LLM-enabled assistants in content generation will facilitate more personalized and targeted content. By understanding and adapting to linguistic nuances and cultural contexts, these tools can help create more engaging and relevant content for diverse audiences.

 2) Retaining the Human Touch in AI-Driven Environments

We know AI won't replace humans but a tool to complement and augment. In the translation and language industry, the advent of AI, particularly in machine translation (MT) and neural MT (NMT), is reshaping roles but not eliminating the human element.

 The shift we're witnessing is not just from traditional source-to-target translation but towards a nuanced role that centers around validating and refining AI output. For example, from the output of the LLM-enabled assistants mentioned before (e.g. Copilot).

 This involves assessing whether AI-generated translations are not only accurate but also contextually relevant, culturally appropriate, and stylistically consistent. The human expertise in understanding linguistic nuances, cultural contexts, and intended messaging remains irreplaceable.

 AI may be able to generate and translate words, but it is the human linguists who ensure those words convey the right meaning, tone, and impact.

3) Ongoing Analysis of MT vs LLM Performance

 Better understanding of how MT performs compared to large language models is another area that will continue into 2024. So far, MT still outperforms LLMs but this will eventually shift over time. Higher-quality LLM output will eventually result in improved accessibility to quality translation and potentially lead to the shift and evolution of NMT to LLM for multilingual content.

4) Deepening of AI Ethics and Governance Conversations

Bias can creep into AI in many ways. Any system trained to make decisions based on training data can have human bias and toxicity baked in. Bias and toxicity in AI and tech is not a new problem but one that is escalating as AI becomes more mainstream. Several national and international AI governance frameworks have emerged over the past couple of years, and managing AI has become a priority for many governments.

Recognizing the significance of ethical AI deployment, industry leaders are taking concrete steps to mitigate biases and enhance diversity in AI-generated output.

 Additionally, companies are implementing stringent evaluation protocols to assess and reduce biases in AI models. Ethical AI guidelines and best practices are being adopted industry-wide to prioritize fairness and accountability, ultimately fostering AI systems that produce diverse, responsible, and equitable results.

5) Advancement of Vendors in the AI Value Chain

 Businesses like Open.AI, AWS, Microsoft, Google, IBM, and Meta will continue to develop and invest in AI and therefore gain ground in the AI value chain. The release of ChatGPT in November 2022 changed the way we think about AI and content development, allowing the average person to write and design anything. It triggered discussion (and some alarm bells) but it also showed us how powerful a product release from these mega-tech companies can be. Key players in the AI tools markets are incredibly influential and can create seismic shifts in how we do things. Especially as their platforms are becoming more user-friendly and affordable, allowing even small businesses and individual developers to leverage powerful AI tools.

6) Increase in AI-as-a-Service (AIaaS)

 In 2024, we are likely to witness a significant rise in AI-as-a-Service (AIaaS) offerings - basically third parties offering outsourced AI. Companies without extensive in-house AI expertise or resources will find AIaaS an invaluable tool in leveraging the power of AI to enhance their operations and competitive edge.

 AIaaS providers will offer a range of services, from machine learning algorithms to NLP and computer vision capabilities, all accessible via cloud-based platforms.

On A Final Note...

 It’s clear that GenAI is not just hype, but a transformative force poised to redefine how we interact with machines, process information, and approach problem-solving across industries. I don't think it will be quite like the classic 80s sci-fi film, Terminator, but the implications of this AI revolution are vast and varied.

(There have been studies into whether LLMs can exhibit feelings, in case you're interested).

From content development to language translation, from maintaining the crucial human touch in AI applications to the ongoing analysis of AI model performance, each aspect reflects a facet of the monumental shift that GenAI is bringing about.

 The question is not if GenAI will go mainstream in 2024, but rather how swiftly and profoundly it will alter the fabric of our digital and real-world interactions. The future of AI is not just knocking on our doors; it's already here, reshaping our world in ways we are just beginning to understand and embrace.

 What do you think? All comments welcome :-)

Thanks to co-author Melissa Gillespie (Bottomley)

#AI #ArtificialIntelligence #GenAI #GenerativeAI #MultilingualContent #Localization #Translation