AI has turn into a pure a part of our each day lives, typically with out us realizing it. From making headlines with feats like Deep Blue to powering the advice engines that recommend your subsequent binge-watch on Netflix, AI’s affect has grown from behind-the-scenes algorithms to a central participant in our each day interactions.
AI can be remodeling our work. Most engineering leaders anticipate utilizing GenAI to construct software program sooner or later, enhancing productiveness throughout all features of developer workflows – not simply in code completion, however in addressing broader challenges corresponding to technical debt, service well being, and cloud price optimizations. By taking up routine duties, AI will enable builders to deal with core areas like enterprise logic, structure, and mentorship.
And it’s not simply engineering groups. Advertising groups can use AI to assist mixture themes from gross sales calls, program managers can use a mixture of AI and automation to construct sturdy timelines and undertaking roadmaps, and crew leads can use AI to generate summaries of dense pages to share with govt management.
To raised perceive this transformation, Atlassian’s Agile and DevOps crew hosted a dialog with two AI specialists: Stacey Law, a Group Product Supervisor who’s spearheading AI work at Atlassian; and Colin Jarvis, a pacesetter at OpenAI, recognized for pioneering developments in generative AI. Each specialists deliver a long time of expertise in constructing cutting-edge tech and leveraging information fashions.
We requested Stacey and Colin how AI is already getting used at this time in firms that make use of information employees, the way it’s affecting staff and groups, and what modifications they count on to see within the subsequent yr.
Listed below are 5 key takeaways from our dialog about real-world AI use instances and the way AI will influence the way forward for work.
Employers wish to use AI to upskill employees – not substitute them
Colin and Stacey continuously discuss to employers about how their organizations take into consideration AI, and opposite to fashionable perception, most employers are not seeking to substitute their information employees with AI. Fairly the other, really.
Many employers are afraid of staff leaving their organizations and taking beneficial information with them. As well as, they urgently wish to upskill their workforce, in each operate, at each stage. They see AI as a software to seize beneficial information and strengthen their workforce – not substitute it.
A number of examples of how AI helps upskill employees:
- Bringing insights and information to them sooner by improved search and defining phrases
- Giving them examples to work from, corresponding to drafting a web page for a sure format or undertaking, primarily based on notes
- Enhancing writing or adjusting tone so as to write for various audiences
- Permitting folks to make use of pure language, as a substitute of boxing them intontechnical languages like JQL or SQL
The most effective GenAI deployments increase people
Whereas nonetheless comparatively new, many firms are already deploying GenAI. Stacey and Colin say one of the best use instances they’ve seen up to now are when AI helps and augments folks, to allow them to do what they’re already doing – however higher. Whether or not it’s supporting analysis or advertising and marketing campaigns or customer support, AI makes folks extra environment friendly and efficient in performing all kinds of duties.
In a single instance that Colin described as a very “unsexy” AI deployment, an organization offered its customer support brokers with an “AI co-pilot” to help them when responding to clients. The co-pilot deployed as a small onscreen window that brokers may simply incorporate into their common workflow. The AI co-pilot rapidly collected and surfaced related details about clients and steered a “subsequent finest motion.”
So what influence did this AI co-pilot have on staff, clients, and prices?
- Worker satisfaction soared, as brokers have been capable of higher help clients (and thus weren’t coping with so many unhappy clients)
- Buyer satisfaction improved, as brokers had extra related info at their fingertips. Your complete expertise was higher and sooner.
- Customer support prices decreased by 24% and agent throughput elevated.
This wasn’t some rocket science utility of AI; it was a easy utility that augmented brokers and made them sooner and higher at their jobs.
AI has the potential to vary work processes and crew collaboration
AI supplies large prospects to vary and expedite workflows and essentially change how groups work collectively.
For instance, one firm used AI to create a advertising and marketing transient generator, the place a person inputs a basic advertising and marketing imaginative and prescient and the applying follows up by asking a sequence of questions and making a advertising and marketing transient. The app may also generate advertising and marketing concepts and supplies for a marketing campaign. At any level, the advertising and marketing crew can construct on these concepts, modify them, or discard them. However this use of AI can do wonders to streamline the advertising and marketing crew’s artistic course of.
Stacey additionally shared thrilling concepts for the way organizations can use AI internally to enhance crew collaboration:
- Have interaction in brainstorming and thought era, utilizing a software corresponding to Confluence.
- Use AI to arrange these unstructured concepts and switch them right into a product requirement doc.
- Leverage AI to translate the product necessities into, say, a Jira undertaking, with tales and acceptance standards.
- Have an AI utility rapidly flip this info right into a presentation.
At every stage, crew members can evaluate, modify, and enhance on what the AI has created, however AI enhances and expedites the method.
One other intriguing risk is to boost collaboration by utilizing AI as a translator – French to English, for instance. A much less apparent however arguably much more thrilling functionality is the flexibility to translate a doc produced by one self-discipline or operate into the language of one other self-discipline or operate. For instance, AI may take a extremely technical doc and translate it into an easier, easier-to-understand, non-technical doc for advertising and marketing or gross sales capabilities.
Small, easy use instances can have a big impact
When firms incorporate AI know-how into their workflows, it’s typically characterised as an enormous transformation – and that’s true. However because the customer support agent use case confirmed, among the most impactful enterprise functions for AI proper now are comparatively easy.
One AI skilled described the next use case: use GenAI as a software to supply quick summaries of conferences or duties. Workforce members save time by self-serving solutions, as a substitute of asking a number of follow-up questions, or ready for a teammate in one other time zone to reply. These inside summaries and self-serve solutions may save every person just a few minutes every day, however over a complete yr, throughout all staff on a crew or in a corporation, the entire influence will be monumental. Easy modifications can yield huge outcomes.
Recommendation from AI specialists: begin small, show success, and scale.
Colin and Stacey inspired people and groups which are considering AI in 2024 to “simply do it.” After seeing AI outcomes first-hand, they challenged groups to consider huge, game-changing use instances that:
- Weren’t potential with out AI. How can AI now make the unattainable potential?
- Have been beforehand potential, however have been very troublesome. How can AI make huge challenges simpler?
For instance, it used to take hours of enhancing time to show a protracted video into shorter clips. However AI-assisted video enhancing saves non-specialists time by producing a wide range of clips and captions, in just some clicks.
Colin and Stacey suggested groups to think about these huge, daring concepts, then get began by operating the smallest checks potential. From these checks, get expertise, study, iterate, and enhance. If and when these checks work, then quickly scale up, double down, and go for it.
Regardless of the numerous fears about AI, we’re optimistic. We imagine AI will in the end change our work lives for the higher – make work simpler, assist groups be extra artistic and productive, streamline our processes, and enhance how we collaborate. And we’re excited to see what’s subsequent.