CTO of Pipedrive with expertise in scaling technology and organizations. Experienced as an innovator, founder and C-level manager.
Here’s a prediction of the astoundingly obvious, followed by a suggestion that is a little deeper than how you might first read it: 2024 is going to surprise the business community with volatile events and is going to need people who work together better to keep up. Let me double down on that “working together better” part.
You can take your pick of dire predictions from high interest rates to global crises, technology disruption and maybe even another pandemic. No one can know what’s ahead, but there’s one safe prediction. Businesses will need to make their workplace and technology experience more human-like if they are to retain the best staff in 2024 to counter these risks.
Using AI isn’t enough—we must create a symbiosis.
Most firms have managed their hybrid working procedures and balanced in-person and at-home working in a fair and useful way for all sides. But those policies and tools that fit 2023 might not fit 2024. Part of what makes great colleagues so great is that they know their worth and stay up to date with developments in their field. They can see industry leaders with smarter ways of working, better collaboration, the right business data to make their lives easy and AI support to remove drudgery. If their own organization doesn’t match up, they’re likely to make the jump.
Why? Both push and pull reasons apply. Remote working can be correlated with loneliness and low morale. Social sciences and psychology are increasingly pervading the corporate world and telling us more about what makes peak and sustainable performance. Screen time isn’t cutting it if we want energized teams that creatively and strategically manage crises and optimize for incremental gains.
People want to work with people, and if organizations can’t help colleagues connect meaningfully for both work and mental health benefits, they will increase their corporate friction. Where colleagues feel that the business makes them toil on easily abstracted admin or rote tasks, they are going to reassess the value the organization sees in them accordingly.
Developers often work together in pair programming to gain some social time as well as learn from each other. I foresee more of these shared working styles growing in popularity among tech teams and across the wider business as workers seek to enjoy the benefits of stronger and possibly in-person collaboration. This may also become a needed training tool as new starters get to grips with humans and AI working together at pace.
Those who acknowledge the relevancy of AI will benefit from it, and those who are not willing to adopt and adapt will lose their advantage.
How you grow AI user expertise is critical.
AI is not “coming for our jobs.” The blended working human-in-the-loop of 2024 will outperform their manual process (or worse—paper-based) competitors. To power that outperformance gap, lowering the time taken to gain mastery will be critical.
Switching contexts from a dry demo or handover document to live, AI-enabled working practices will be an increasing challenge. It will be much easier to onboard new colleagues if they can just watch, copy and talk live to a connected human working in the middle of their personalized automation setup.
Thousands of years of teaching and training show that teachers and coaches are vital to helping increase the uptake and use of education—and businesses must pay attention to this foundational aspect of the AI-enabled work experience. Creating the right feedback loop for AI and automation research, testing, training, integration and ongoing evaluation will become a critical differentiator in outperformance to come.
In our growing human-AI cooperation, the people and organizations that can build trust between them and AI will move faster and succeed more. That means that humans have to learn to trust AI. Industry must make that easier for users, their organizations and society to do with explainability and guardrails. This trust element applies to programming in pairs, for example. There’s an educational and social aspect that offers the best results when there is strong respect and trust between the parties.
Communication remains the most important skill and process.
McKinsey published a blog post covering “contributory dissent.” They called this article “How to master communication in problem solving.” Communication is likely to remain one of the most important skills in a more AI-driven world, as shaping outputs, finessing messages and collaborating through uncertainty are all inherently messy activities that benefit from multiple stakeholders with diverse points of view and experiences.
Contributory dissent can act as a safety valve before the AI-driven flywheel takes off or goes too far. With the speed and scale that AI-driven activity takes off, rapid reactions to poor performance are a must. Modern organizations must not stand on hierarchy or a regularly scheduled review cycle when there’s an indication of possible harm, or even inefficiency, given how mistakes or friction will compound.
Succeeding means outperforming on the basics and value-add.
Much best practice advice is quite simple, and yet falls by the wayside. It’s hard to get the basics right all the time. AI will increasingly support and guide teams in getting the basics right just as much as it will supercharge decision-making and increase the value-add of business offerings at the high end.
The good news is that getting ready for AI, or for any other kind of new and improved ways of working, means simply improving the quality of institutional thinking, collaboration and delivery—and of course, codifying and passing those practices and skills on much more effectively.
Whatever the future holds, these practices are achievable very quickly—if leaders apply themselves to a deep and genuine process of business transformation that incorporates the best of what colleagues can do now, and with the right support.
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