What a year it has been for those of us interested in the future of work and smart organisations!
We have seen incredible developments in AI tools and LLMs, culminating in the preview release of OpenAI’s new o3 reasoning model last week.
The tech is developing faster (and at great expense) than our ability to absorb it and adapt to it, and nowhere is this more obvious than in the enterprise.
Next week at the year end, we will look forward to 2025 and consider the huge opportunity in front of us to massively reduce the costs of doing business, whilst at the same time putting people front and centre of the way work is done. This could re-vitalise struggling private and public sector institutions, but it will also catapult small, imaginative teams to the top of the value creation league by allowing us to do much, much more with less time, resource and bureaucracy.
But for now, here is a wrap up of 2024 from all of us at Shift*Academy, with some actionable insights and practical implementation playbooks and techniques that might come in handy in 2025.
TL;DR
I asked ChatGPT to summarise what we wrote about in 2024:
“In 2024, ShiftAcademy extensively explored the integration of artificial intelligence (AI) into enterprise operations, emphasizing practical applications, organizational readiness, and the transformative potential of AI technologies.”*
It listed our key topics in 2024 as:
- Enterprise AI Implementation and Case Studies
- Advancements in AI Capabilities
- Organizational Readiness and Cultural Adaptation
- Enhancing Productivity and Operational Agility
- Strategic Metrics and Competitive Intelligence
- Future Outlook and Continuous Improvement
Twelve Insights for the Holidays
Here is a human-curated selection of key articles from each month of 2024:
We started 2024 predicting it would be a big year for enterprise AI adoption, but also that we need to think long-term and not be driven by either the hype or the backlash to the hype.
In February, we focused on AI’s productivity potential, if it can avoid the Solow Paradox; how it can help re-invent middle management; and, how we think AI could catalyse previous waves of change in organisations.
In March, we looked at the implementation barriers organisations need to overcome with people and adoption issues, org structure, tech stack limitations, and a lack of connected data and knowledge.
In April, amid lots of ‘inside baseball’ noise about OpenAI, we recommended not to focus on the theoretical goal of AGI when we already have the tools to transform work, for example by creating hybrid centaur service teams that make the most of people + AI/automation.
In May we looked at how organisations should organise cross-functional efforts to guide AI adoption, and shared this deep-dive playbook from our curriculum on how to form and run a Digital Leaders Group to oversee your capability roadmap and ensure alignment across major functions.
In June, we wrote about how AI is already unbundling tasks and management, and how this could lead to a re-bundling of task automations coordinated by agents, rather than just enterprise apps and chatbots.
Instead of taking to the beach in July like normal people, we dug into how AI could help defeat the “meeting-industrial complex” by creating an architecture of collaboration involving the best of people and AI agents as a way to solve the problem of coordinating work at scale without burying value creation below a bureaucratic hierarchy.
This piece from August argued that the OpenAI drama remained an annoying distraction from the fact that existing LLMs and even SLMs are already enough to automate a great deal of boring repetitive tasks, and we some thoughts on how AI will shift its focus from individual components to products & systems.
This piece from September considers how human and machine languages have co-evolved to enable us to program with prompts, and soon perhaps we will be able to program organisations in the same way – the only limit (and perhaps the key skill) is the ability to ask better questions to define our goals as clearly as possible.
One paradox of AI that we wrote about in October is how slowly enterprise use cases are advancing compared to personal productivity use cases, and we looked at the ‘secret cyborg’ phenomenon and new hybrid AI roles, plus how connected knowledge repositories will be force multipliers for enterprise AI.
This piece from November considers how AI will finally mean the digital workplace (rather than stuffy meeting rooms) is where work really happens, and what this might mean for the enterprise software sector. Will we see a shift back to more in-house development?
In December, we looked at how LLMs are becoming just one component of AI systems as we move beyond a focus on synthetic content towards agentic automation and decision making. Will this remove the need for old-fashioned manual management, or will managers use AI to generate more work rituals and processes to justify their roles?
Practical Techniques and Playbooks
For our premium subscribers and practitioners, we shared some meaty, practical pieces to help guide implementation – an incredible value proposition (and easily expensable!) for any leader or manager interested is going deeper into the role of AI in organisational improvement.
Six digital business capability maps:
Six advanced management techniques for organisational change:
Six deep-dive case studies of new ways of working:
If you haven’t yet upgraded, here is a very special time-limited offer to experience our full premium edition