When almost every business is facing pressure to adopt AI technology, knowing that it is actually the right move and how to proceed is the real challenge.
The term AI is overthrown, but it is important to recognize that it refers to a vast and diverse range of technologies and processes. So while most companies in some range are investigating AI, knowing what to do with it is a completely different matter.
While current generation of AI technologies are in a mature state as most organizations are now aware of their ability to increase productivity, software company Atlassian is trying to make sure they see authentic returns in AI investments, beyond increasing individual efficiency in tasks like drafting emails or writing simple code.
In a recently published AI collaboration index, Atlassian looks at how companies incorporate AI and why the actual benefits available from technology are completely different, even if individual staff improve productivity.
Improve AI productivity
According to a study by Atlassian, daily use of AI tools for workers has doubled over the past year, with at the individual level, practices have increased output by 33%, saving average employees about 1.3 hours per day.
In addition to speeding up the completion of daily tasks, the voted workers said they were able to save time in areas such as process improvement, strategic thinking, planning and professional development.
Increased productivity is not enough
Despite the clear benefits of workers using AI, business leaders, asked by Atlassian, overwhelmingly agreed that there have been few meaningful ways to change since incorporating AI processes.
In fact, only 3% reported “transformational change” from the AI process, despite claiming that they consider employee productivity to be a major indicator of whether investments in AI have paid off.
In fact, this hyperfocus on personal productivity can make companies less likely to achieve dramatic innovation.
“Yes, AI can save time by writing code and drafting emails. But most teams are still owned on tasks. Plus, the ever-growing wave of AI tools. The silos last. Work is split across the platform. The goals are cut off.
“Although organizations are seeing increased productivity in isolated AI-enabled areas, these benefits have not led to significant improvements in efficiency, innovation, or work quality across the company.”
There's no doubt about AI
Part of the problem, according to executives asked Atlassian, is that in many cases AI has led the team in the wrong direction. This is probably the result of the frequently criticized psychophantistic nature of popular chatbots, which could lead to cases where AI agents can overapprove.
Also, the AI hallucination problem remains, but perhaps less common than what was seen in the first release of ChatGPT, but it still has problems.
The report found that 42% of employees who used AI at work trust the output without checking accuracy, often due to time pressure.
AI adjustment
With the report established, around 97% of companies do not consider AI to be transformative, raising the question of what a small number of people are doing right.
This report identifies key factors that will lead to successful AI implementation, among other things, establishing a company-wide knowledge base.
This is essentially a practice that ensures that insights related to or generated from AI will be used to support the entire team and internal AI tools.
“AI can only act on what is accessible. If knowledge is shared only in side conversations or is trapped in silos, AI cannot actively spread those insights across the organization,” Sands said.
This can be achieved fairly simply by ensuring valuable insights that team members collaborating on digital whiteboards and shared spaces can provide context to essentially corporate AI agents, including meeting AI note takers.
The report also encourages AI systems to focus on relevant tasks and set clear, documented goals on the centralized platform to encourage all team members to improve their coordination with increasing use of AI.
Ultimately, this report determined that this broader idea of adjustment is a key factor in making the most of AI tools. While individual uses can speed up minor tasks, collaboration, standardization and adjustments can make much greater differences.
“If adjustments are not the focus, pinning them to individual productivity can exacerbate existing issues,” Sands said.
“People can work with AI to complete tasks more quickly, but they don't stop thinking about whether they're doing the right task.”
