The end of 2022 was the end of the AI conversation. The conversation that said: "AI isn’t a valid solution, yet." Then the first ChatGPT headlines appeared: ‘The brilliance and weirdness of ChatGPT’, ‘ChatGPT is a tipping point for AI’, and ‘What is AI chatbot phenomenon ChatGPT?’
Little did these publications or headlines realise that less than a month later, ChatGPT would be the fastest growing application of all time, outstripping every other innovation’s adoption statistics by a hot mile. So, as the digital realm sits poised on the precipice of a new year, the question is simple – is there another ChatGPT phenomenon only a press release away?
Probably not. The digital realm is still picking up its skirts as it navigates through the complex landscape introduced by highly agile and functional generative AI solutions such as ChatGPT, Microsoft Copilot, Google Bard and GitHub CoPilot. Which means that the top trends for 2024 are likely shaped around how organisations and solutions will evolve and adapt around AI and its still largely untapped potential.
These trends reflect the evolving landscape of data analytics with a focus on accessibility, transparency and the integration of advanced technologies. AI will remain increasingly prevalent alongside machine learning in data analytics, while hybrid and multicloud technology will tap into AI to deliver even more relevant flexibility and security.
The biggest trends that will likely roar onto the scene over the coming year are:
01: Data democratisation will continue to gain traction, allowing for non-data literate professionals to gain access to data insights on demand. This will improve decision-making and visibility into performance and KPIs and will have the added benefit of transforming customer experiences.
02: Emerging technologies and the shift to cloud and innovation are not just changing the operational dynamics within the business, but the people ones too. The human factor will continue to gain traction when it comes to investing into technology or getting the most from existing technology investments. Organisations will remain focused on adjusting legacy patterns of work and approaches so they can woo the talent that they need to optimise growth and innovation.
03: Skills, skills and upskills. Organisations need skilled people to make the most of AI. This isn’t just a team of hardcore Python developers kept safe and nurtured within the business. No, this is talent that has an in-depth understanding of AI, its impact, incoming trends and technologies to watch so that the business can re-align and adapt on demand. Plus, when people feel confident with the technology, their adoption rates are higher and the use cases more successful.
04: Edge analytics and augmented analytics will step into the limelight. Augmented analytics, combining AI and natural language processing (NLP) will create more user-friendly analytics tools, which will again drive data democratisation. Edge analytics will bring real-time data processing at source, which will add value to augmented analytics by increasing the speed to decision-making.
05: Data observability, governance and ethics will remain a priority for organisations. The emphasis on ethical data usage and compliance will remain high, particularly in light of AI’s impact, and this will play a role in enhancing the monitoring of data to ensure quality, reliability and compliance.
06: Continuous intelligence and XAI will become headline news and business must-haves. XAI (explainable AI) will make AI models transparent and accountable, while continuous intelligence will make real-time data more accessible for improved decision-making.
07: Data, data, data and some more data. Data for social good will continue its trajectory as data is used to address global challenges; data storytelling will tell insights more effectively and change the dynamic of data accessibility; data security will continue as a priority; and DataOps will streamline data pipelines for agility and reliability.
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