The mainstreaming of generative AI in 2024 has evolved beyond initial experimentation. While large enterprises are integrating AI into core operations, smaller organisations have gained valuable experience through accessible tools like ChatGPT. Looking ahead to 2025, the focus is shifting from hype to practical implementation, as organisations develop more nuanced AI strategies. Tech leaders will look to prioritise adoption in scenarios where AI can deliver measurable business value, moving from broad exploration to targeted proficiency for maximum impact.
iManage executives, Alex Smith, Global Search & AI Product Lead; Paul Walker, Global Solutions Director; and Jack Shepherd, Senior Principal Business Consultant; offer views on key AI trends for 2025:
Alex Smith, Global Search & AI Product Lead, iManage:
From hype to impact: AI will need to prove its worth
As the dust settles on the AI of 2024, a new reality will dawn for CTOs and innovation leaders in 2025. The days of experimental AI projects and playful applications are over. In 2025, they will need to demonstrate tangible, bottom-line results from the AI investments made in 2024.
Already, boardrooms across industries are beginning to demand more than just novelty. They want to see AI drive efficiency, boost productivity, grow sales, enhance profitability, and open new revenue streams – at least in some combination. The professional services firm that may have proudly unveiled its ‘cool’ AI chatbot must now integrate it with robust search capabilities, ensuring it delivers actionable insights and measurable outcomes.
CTOs will find themselves challenged to transform AI from a groovy toy into a powerful tool that reshapes business operations. Only the AI initiatives that demonstrably strengthen the organisation’s bottom line will survive and thrive. Those CTOs who falter in this endeavor could well see their AI budgets slashed. A nice-to-have add-on may simply prove too expensive to sustain.
“Search” will make a comeback in an AI-driven world
In a rush to embrace AI, many organizations have mistakenly equated it with search technology. As the understanding of AI and search technologies advances in 2025, organisations will recognise that AI and search are not competing technologies, but complementary tools, each with their own strengths and applications. This revelation perhaps even today will come as no surprise to those who’ve wrestled with AI tools like Copilot, finding them lacking in search capabilities.
As this initial disappointment gives way to a more nuanced understanding of these technologies, in 2025, the adoption of sophisticated search technology will grow further in importance. Software developers will incorporate new developments such as semantic search and retrieval augmented generation in their solutions, coupled with nifty natural language capabilities to help knowledge workers quickly and efficiently find the resources they need to do their best work and deliver the best outcomes.
Paul Walker, Global Solutions Director, iManage:
The prompt revolution – this is how enterprises will master generative AI in 2025
In 2024, we watched generative AI evolve in sophistication. Today it can churn out everything from compelling text to intricate images and complex software code. Yet and perhaps curiously, many enterprises find themselves struggling to harness the full potential of tools like Microsoft Copilot, arguably the most advanced and comprehensive generative AI tool available. User error perhaps?
The art of unlocking the full power of generative AI lies in the art of crafting the perfect prompt. The more specific and well-defined the query, the more useful the output. Prompts are truly the last mile connections linking employees to the knowledge residing in the organisation for informed and faster decision-making.
Recognising the need for this critical link between the technology and the user, prompt engineering and prompt management will emerge as a generative AI best practice in 2025. Enterprises will carefully develop and curate prompts running into the 100s and 1000s, covering a wide range of common and specialised queries. This shift towards enterprise-level prompt engineering will transform the way employees interact with AI tools. With a mere click of a button, they will select from a menu of pre-engineered prompts, each tailored to extract specific insights or generate particular types of content.
AI-powered information self-service will become a reality
Speak to any business department head (legal, compliance, HR, IT, procurement, support desk, security, and the list goes on) in the enterprise and they will likely lament the countless hours lost responding to repetitive information requests from employees and internal stakeholders. Now with generative AI, in 2025, AI-powered self-service solutions will become a reality, potentially revolutionising how employees access and utilise information within enterprises. Advanced natural language processing will enable intuitive, conversational interfaces that understand context and intent, allowing staff to query complex data sets and receive relevant and reliable insights.
As AI self-service tools become more sophisticated, enterprises will see increased productivity, reduced support costs, and improved employee satisfaction. However, this AI-powered future won’t come without challenges. To fully benefit from this approach, enterprises will need to prioritise data quality and architecture to ensure their self-service AI-powered solutions have access to accurate, up-to-date, and reliable information.
Jack Shepherd, Senior Principal Business Consultant, iManage:
Focus on gen AI return on investment
It is two years since the world became enamoured with ChatGPT and generative AI, and since then, the focus on law firms and legal teams exploring the impact of AI has been relentless. Organisations have increased their innovation and technology budgets to make sure they are not missing out on the opportunities AI might bring them.
Yet two years on, many organisations have struggled to move beyond the stage of learning what generative AI is, how it works, and what benefits it might bring. While the industry is still very excited about generative AI, we have seen 2024 bring more realism. This has occurred in discovering where generative AI might be best deployed and where its use should be avoided.
In 2025, we should expect to see fewer resources allocated to exploring AI for the sake of it and more focus on its return on investment. Generative AI is not immune from the harsh reality that any technology is only as powerful as the value it actually delivers.
Agentic AI is on the cards
Perhaps all of this explains why proponents of AI have been so focused on renewing the excitement in AI through exploring what agentic AI might deliver. Agentic AI is nothing new per se but represents a new way of deploying generative AI models – specifically by allowing LLMs to take a prompt, and break down its response into a series of steps that it feeds back into itself.
Agentic AI has the potential to be transformational as well as a huge disappointment. Those deploying it sensibly will combine it with process design, looking at a process holistically, breaking it down into steps, and deploying agentic AI in steps where a more nuanced and flexible approach is appropriate.
Those who treat agentic AI as a silver bullet to solve any process will be sorely disappointed. Throwing agentic AI at a process without thinking about whether the process needs a complete redesign will result in chaos and inconsistency. These are things most departments and teams should be trying to avoid.
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