UST, a digital transformation solutions company, has launched a massive new initiative to train over 25,000 of its employees globally in Generative AI (GenAI) and provide opportunities for career advancement. This ambitious program underscores UST’s ongoing efforts to comprehensive workforce training and upskilling, keeping its talented personnel future-ready, the company stated. 

The program comes just months after the unveiling of UST AlphaAI, which consolidates the company’s AI offerings to enhance business agility, streamline operations, and accelerate digital transformation journeys.

UST will offer a range of GenAI training programs that are specifically tailored to its employees and their different roles and responsibilities, improving efficiency while helping each employee reach their own unique potential. 

The training program will build upon insights gained through UST’s collaboration and partnership with AI researchers from renowned academic institutions such as the MIT Computer Science & Artificial Intelligence Laboratory and the Stanford Artificial Intelligence Laboratory. This legacy of close collaboration with leading researchers will help UST expand on its culture of continuous learning by bringing the latest academic breakthroughs to its workforce, according to a press release issued by the company. 

“Our comprehensive GenAI training initiative will set a new industry standard and bring over 25,000 employees up to speed on everything from foundational GenAI concepts to cutting-edge applications. Adaptable and customizable for each participant, the flexible training program provides hands-on experience with industry-leading tools and platforms like GitHub Copilot, setting our employees up for future success by ensuring that they can apply GenAI capabilities across diverse domains, said Sunil Balakrishnan, Chief Values Officer and Global Head – Development Canter Operations, UST.

“At UST, we recognize that the key to staying competitive in today’s fast-paced digital landscape lies in the continuous upskilling of our workforce. As GenAI continues to revolutionize industries and transform business operations, we remain dedicated to equipping our employees with the tools and knowledge they need to leverage these cutting-edge technologies effectively,” said Dr. Adnan Masood, Chief AI Architect, UST.

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Generative AI or GenAI has perhaps had the fastest uptake in the history of enterprise with vast majority of the organizations trying to leverage the technology for various use cases. According to Gartner, more than 80% of enterprises will have used GenAI APIs or models, or deployed GenAI-enabled applications in production environments by 2026, up from less than 5% in 2023. But to get there, enterprises have an uphill task ahead of them. 

In an email interview with CIO Dimension, Lakshminarasimman Raghavan, Group VP Technology, Publicis Sapient, shares what it takes to advance GenAI projects from PoC to production. 

Edited excerpts: 

Majority of the GenAI projects in 2023 focused experimentation and proof of concepts. Do you see GenAI use cases moving from initial pilots and PoC to production this year?

As GenAI emerges as a fundamental capability for IT organisations, there is a pressing need for a transformative shift in capability development. Building Gen AI capabilities in-house is imperative to keep pace with the rapid evolution and widespread adoption of this technology across various industries. While trying out new technologies through PoCs shows what’s possible, true insights emerge when solutions are deployed into real-world scenarios. To effectively test and refine solutions, the time spent on PoCs must be streamlined. 

IT leaders can direct their focus on specific challenges, working to transform them into tangible realities. This approach facilitates the rigorous testing and refinement solutions within live environments.  Many of the organizations that we work with are in the PoC stages with some of them starting to rollout their solutions to production this year.

What are some of the key GenAI trends that will emerge and dominate through the year? 

GenAI is expected to unlock new opportunities for automation, efficiency, and innovation across enterprise operations, leading to significant advancements in various domains. Here are some key trends:

• Automated code generation: GenAI will revolutionize software development by accelerating code creation processes. This will lead to more cost-effective and rapid development cycles, enabling IT organizations to deliver solutions more efficiently.
• In-house GenAI capabilities: Organizations will increasingly invest in developing in-house GenAI capabilities to address specific challenges and enhance operational efficiency. This shift will reduce reliance on external partners and vendors, allowing companies to have more control over costs and resources. These capabilities not only include just technical aspects but also aspects such as knowledge in biases, ethical aspects and operational aspects such as testing, optimizing and tuning GenAI solutions etc.
• Transformation of talent landscape: The emergence of GenAI AI as a core capability will transform the engineering and IT talent landscape. Skilled professionals with expertise in GenAI will become indispensable, driving the adoption and implementation of this technology across various industries.
• Focus on scalable solutions: IT leaders will prioritize scalable solutions over PoCs to harness the full potential of GenAI. By implementing and refining solutions in live environments, organizations can derive real insights and drive tangible outcomes, rather than investing time in experimental trials.
• Streamlining of data: The fundamental building block of any GenAI based solution is the underlying data ranging from code all the way to behavioral and transactional data. Organizations will need to invest in streamlining their data to enable effective GenAI implementations. 

A transformation in the engineering and IT talent landscape is anticipated, with Gen AI skills emerging as essential. A new wave of engineers will rise, armed with the expertise necessary to unleash the potential of this technology. Organizations are expected to internalize GenAI endeavours, driven by the imperative to manage costs and bolster operational efficiency, diverging from sole reliance on public cloud infrastructure.

What could potentially be the top challenges for CIOs as they try to deploy GenAI at scale within the enterprises?

A few aspects that CIOs must consider while deploying GenAI at scale include:

• Aligning with business goals: CIOs must seamlessly integrate transformative technologies, like GenAI, with business objectives. This requires a proactive approach to understand GenAI’s influence and equip teams with the necessary tools to outline viable business cases. The challenge lies in decoding GenAI’s impact and aligning technological advancements with overarching business imperatives.
• Prioritizing data engineering: Establishing a robust Core Data Architecture is crucial for adapting to the evolving tech landscape. CIOs are prioritizing efforts in data engineering, focusing on tasks such as formatting data appropriately, optimizing data locations for model training, and assessing existing data platforms. This concentrated attention and investment in data engineering are essential for leveraging GenAI effectively.
• Building in-house capabilities: Developing in-house GenAI capabilities requires significant investment in talent, resources, and infrastructure. CIOs need to evaluate the extent to which they rely on external partners and vendors versus building these capabilities internally. Securing the necessary talent and allocating resources to sustain and evolve these capabilities over time presents a considerable challenge as well as opportunity. This involves evaluating the costs, talent acquisition, and resource allocation needed for either approach.

These factors underscore the need for CIOs to strategically align with business teams, emphasize collaboration, and proactively decode GenAI to ensure successful deployment at scale while navigating the complexities of organizational transformation and technological advancement.

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Borderless AI, the AI-powered startup in the Employer of Record (EOR) space, announced that it has raised $27 million in seed funding to leverage the power of generative AI to automate and accelerate the process of onboarding, managing, and paying international team members. The company maintains that its AI agent, Alberni, can solve complex problems and automate processes in any country around the world within 10 minutes; the market norm is 7-10 business days.

The $27 million seed round was led by Susquehanna and Aglaé Ventures, the venture arm of Bernard Arnault, currently the richest man in the world, with participation from additional institutional investors. The company was founded by serial entrepreneur Willson Cross and Lyft’s founding investor Sean Aggarwal. Borderless AI’s launch comes at a time of increased investment and interest in vertical-specific AI, with numerous companies like Harvey for legal services and Sierra for customer service, leading the way and drawing attention to the critical need for AI agents across verticals.

“As the first company in the world to bring AI agents to HR, we are firm believers that AI agents will become commonplace for companies just like websites in the 90s and mobile apps in the 2000s,” said Willson Cross, Co-founder and CEO of Borderless AI. “Leveraging conversational AI, our platform automates many of the complexities within the global HR stack, without hallucinations, such as payroll set-up, time-off requests, or employment agreement generation. Our AI is fluent in a multitude of languages, allowing for geographic expansion and successful deployment of business operations around the globe.”

Alberni is available in 170 languages and cuts the time it takes to generate employment agreements, allowing a company’s legal and HR teams to move faster, save money and ensure compliance in the onboarding and payments processes. Alberni can also answer complex employment law, finance or tax queries, an important need for the distributed global workforce and employers looking to scale quickly.

“Our mission is to bring economic empowerment to the world,” said Sean Aggarwal, Executive Chairman and Co-founder of Borderless AI. “With our AI first approach to HR, we’re removing geographic barriers and democratizing access to the best job opportunities for talented people around the globe, and we’re excited to see the possibilities it opens for employers and employees alike.”

Borderless AI is serving organizations of all sizes and across industries, and claims popular dating app Raya; MG2, a 500+ employee-size, global architecture firm; and Affiniti, a venture-backed fintech startup as customers.

The company worked with Omeed Malik and his investment bank, Farvahar Partners, in raising the majority of the round.

Borderless AI is also a strategic partner of Large Language Model (LLM) leader Cohere and is the only partner deploying Cohere’s models to global HR. Borderless AI has developed its proprietary data platform that augments Cohere’s LLM, putting trust and accuracy at the forefront of the technology.

“The HR industry is ripe for innovation and Borderless AI is one of those companies that has the rare combination of industry expertise, product innovation, and a deeply committed and capable founding team,” said Miyuki Matsumoto, Partner at Aglaé Ventures. “Globalization isn’t going anywhere and companies will rely on seamless technology like Borderless AI and Alberni to help them scale successfully on a global level. We strongly believe that AI agents for HR will become mainstream and we’re thrilled to be a part of this journey.”

With an increased demand in technologies that help companies navigate complex issues that arise from hiring international team members, such as employment agreements and employee tax forms, Borderless AI’s technology is a key differentiator in the EOR market, accelerating the future of work and allowing companies to understand complex queries that previously took days or weeks to navigate.

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A new forecast from Gartner indicates that Generative AI is all set to transform the cybersecurity space in India. The emergence of generative AI (GenAI) has caused one of the biggest disruptions in digital and business sectors in the last couple of years. “Through ethical, safe and secure implementation of this technology, CISOs can improve the performance of their security functions and enhance organizational resilience,” said Abhyuday Data, Director Analyst at Gartner. 

While managing GenAI presents inevitable challenges, there are also external factors to consider, such as regulatory concerns and the rapid adoption of cloud computing.

To effectively handle the combined impact of these forces and enhance their organization’s cybersecurity program in 2024, Gartner recommends that CISOs in India must prioritize two top cybersecurity trends:

GenAI Transforming the Cybersecurity Market: GenAI introduces new attack surfaces requiring  changes to application and data security practices and user monitoring. Gartner predicts that by 2025, GenAI will cause a spike in the cybersecurity resources required to secure it, causing more than a 15% incremental spend on application and data security.

Gartner analysts said organizations should conduct proof of concepts before incorporating GenAI into their cybersecurity programs, beginning with application security and security operations. A policy for overseeing the introduction of GenAI-based products into the organization must also be established, to ensure that all internal teams using this technology understand and adhere to a set of unified policies.

Bridging the Communications Gap with Cybersecurity Outcome-Driven Metrics: Outcome driven metrics (ODMs) are central to creating a defensible cybersecurity investment strategy. They provide a credible and defensible expression of risk appetite that supports direct investment.

“ODMs enable SRM (security & risk management) leaders to convey the value of cybersecurity investment beyond the importance of regulatory compliance,” said Data. “Organizations seeking an approach to measure cybersecurity value that resonates with executives and supports practical investment decisions must adopt ODMs.”

Spending in security to grow

Gartner forecasts that end-user spending on security and risk management (SRM) in India is expected to total $2.9 billion in 2024, an increase of 12.4% from 2023. 

Indian organizations will continue to increase their security spending through 2024 due to legacy IT modernization using cloud technology, industry demand for digital platforms, updated regulatory environment, and continuous remote/hybrid work.

In 2024, cloud security spending in India is projected to record the highest growth. The adoption of cloud and multi-cloud presents security challenges, causing an increased focus on cloud security by Indian organizations.

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In November 2021, when IBM spun off its infrastructure services to create ‘Kyndryl’, there were quite a few naysayers. Many called it the unshackling of an unwanted part of the business with declining revenues and earnings. Two challenging years down the line, Kyndryl seems to have done a lot of things right. It’s third quarter fiscal 2024 earnings stand as a testimony. 

It beat Wall Street’s expectations, cut its losses by 50% and raised full-year outlook, increasing its stock value by more than 12%. Its 10% revenue decline is attributed to the strategic exit from zero-margin, low-margin revenue streams. At the time of spinoff, about 40% of its contracts were reportedly making little or no profit. 

In Q3 FY24, the company reported double digit growth in its consult revenue, indicating a strong growth in high-margin services. It’s clear that Kyndryl is shedding businesses that added little or no value, and becoming more focused towards areas where it sees higher margins and potential for growth. 

Quite understandably, it was an uphill battle to turn things around, says Karen Forbes, Vice President – Global Go-To-Market and Customer Advocacy at Kyndryl, during her recent visit to Bangalore. 

CIO Dimension caught up with Karen to know more about Kyndryl’s transformation journey. 

Edited excerpts: 

It’s been over two years since the spin off and it’s been a mixed bag, which is not a surprise after a big spin like this. How would you summarize the last two years of Kyndryl’s journey? 

It has been a big journey for us to embed the brand in the market as we stand alongside some of the giants. We had to build a services company that was unshackled by a product company. Two years down the line, we can say with conviction that we are not a legacy spinoff losing money. Our business results clearly project that now. Besides, we are in the new areas of market, we have built new practices and capabilities and are growing those capabilities in our customers. 

Our leadership had two key mandates for us during this massive transition. The first one is to look after our customers, most of whom agreed to stay with us. Secondly, we decided to retain every employee and give them the confidence to come across. Our leadership has done a fantastic job in steering us through that journey.

Two years ago, when the spin was announced, I don’t think many people were placing the bets on us. There was a lot of cynicism out there. But what we achieved in two years is phenomenal and each of us is proud of it. 

Preparing an organization with about 85,000 employees worldwide during a transformation of this scale is not a small feat. What are your learnings? 

The cultural journey has been challenging because we are changing hearts and minds. We were focusing on building confidence among our people. We spent a huge amount of time talking to them about the brand of Kyndryl, the purpose and mission of the brand. 

We created something called the ‘Kyndryl Way’ which talked about the changes we must embrace as we become a services company. For example, most of our teams on the ground never had to work with channel partners or alliances before. We had to teach many new skills to our teams and build trust because this different way of engaging with customers was not usual for us in the ‘old co’. 

The second big vector is our 3A’s strategic objectives that are at the center of our transformation, which is around Alliances, Advanced Delivery and Accounts. We have been making steady progress in all these areas. Our Alliances with tech leaders like AWS, Google and Microsoft have helped us expand our addressable market. Kyndryl Bridge platform has roughly 750 customers performing over 1 billion automations, generating annual savings of $500 million.  

Kyndryl’s hyperscaler partnerships are a significant part of your growth strategy. Tell us a bit more about these alliances. 

We exceeded our alliance revenue targets, with over $300 million generated this year and raised our full fiscal year target to $400 million. We increased our cloud-related capabilities with 38,000 hyperscaler certifications.

Clearly, there is a lot going on in the cloud space. We work with the hyperscalers to help customers understand what their cloud strategy must be VS leading them to a particular hypervisor.  We work together a lot to understand what we can deliver to customers around data management, Gen AI, sustainability, hybrid cloud, FinOps and much more. Some of these areas help us build relationships beyond CIOs to include CFOs, data managers among others.  As our revenue is historically shrinking, it’s important to be in those new places. 

We are also building specific solutions and reference architectures around different industries like financial services and technologies such as genAI and analytics with each of these hyperscalers. So, we are moving the partnership beyond the cloud migration aspect to larger areas. 

How are you modernizing your GTM to align with the new ways of doing things? 

We have been focusing on simplifying how we show up in front of the customer. For example, instead of having multiple specialists as multiple touchpoints, we try to be more cross-practice to solve the customers’ business problem. We start with changing the narrative by focusing on ‘Innovate, modernize and secure’. It’s kind of a flip on from being a product company where you walk in and talk about the products that you like to sell. 

We had an agreement with IBM to use their process and technology at spin. In the last two years, we completely modernized and transformed our front & back offices to “fit-for-purpose” modern IT infrastructure. This helped us consolidate over 80% of the application portfolio we inherited, from over 1,800 business applications to fewer than 360 applications. That made us more efficient and effective in the way we go to market. 

The third important part of the GTM is the skills. We continue to invest heavily on the skills of our people. People are the heart of what we do and they are our most valuable asset as a services company. 

Lastly, would you like to talk about some interesting customer stories from India and the significance of India as a market for Kyndryl? 

India is a particularly exciting market for us. Some of our key customers in India are from the banking and financial sector. A notably big win for us from this sector is Canara Bank which partnered with us to manage and transform their IT operation including the application landscape. We also work a lot of with small finance banks like Suryoday Bank for technology transformation and digital banking. NPCI is another key customer for us, helping them manage their data centers which handle up to 70 billion transactions a month. 

We have some really inspiring stories from our customers like Honda Motorcycle & Scooter India, USDC / Jain University and Dr. Lal Path Labs from India. Most importantly, what we see in India is a market where we can innovate in and scale for the rest of the markets globally.

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2023 saw organisations witness unprecedented levels of cybercrime. Palo Alto Networks’ State of Cybersecurity survey found that 67% of Indian government/essential services witnessed more than 50% increase in disruptive cyberattacks in 2022–2023. In October 2023, the firm received the most number of calls to their incident response team ever. Cybercriminals have used ransomware to target critical infrastructures and found novel techniques to exploit emerging technologies like generative AI to ill-effect. 

The State of Cybersecurity survey also found that 75% of Indian organisations have increased their cybersecurity budgets in 2023 compared to 2022. With Indian organisations investing more within cybersecurity, it’s critical this money be spent wisely.

Predicting cybersecurity trends for 2024 will be especially important if organisations want to get ahead of modern cyberattackers. With stakes higher than ever, organisations need to take a holistic approach – accounting for macroeconomic factors, emerging technologies, and cloud risks among others.

Ian Lim, Field Chief Security Officer, Palo Alto Networks, said, “In 2023, we’ve seen mature organisations, who invest heavily in cybersecurity, still falling victim to debilitating cyberattacks. This is due to the tenacity and ingenuity of attackers who exploit cyber hygiene issues or find novel ways to compromise legacy defences. Another key reason for these breaches lies in the complexity of security capabilities in most modern organisations. They use an average of 31.58 disparate security tools to protect their highly interconnected and innovative environments. The lack of correlation and the level of noise generated by these tools creates immense visibility gaps and dampens their ability for detection and response.”

He added, “Going into 2024, highly motivated cybercriminals, nation state attackers and hacktivists will continue to innovate, expand and exploit – not much we can do to slow that down. However, we could and should definitely address the complexity of our security capabilities with AI to make them more effective and cost efficient.”

Here are the five cybersecurity trends to watch out for in 2024:

1.        Hacktivism: the modern crusade 

2023 saw numerous instances of broadcast events being disrupted by climate activists. This year, this protest could take the shape of a cyber-first campaign. With significant events like the Olympics, the Euros, and regional elections coming up, hacktivists will look to further their cause to audiences in the millions. Previously, a high level of technical expertise was necessary, but the cybercrime-as-a-service model has lowered this threshold. Now, it only takes an extremely motivated activist with sufficient funds.

Tumultuous geopolitical climates will provide opportunities for hacktivists to gain notoriety for their group and sympathy for their cause. Most hacktivist activity is via Distributed-Denial-of-Service (DDoS) attacks. For example, during the G20 Summit in India, more than 30 groups of hacktivists from neighbouring countries attacked more than 600 websites of government and private entities through DDoS attacks, defacements, and data leaks.

In 2024, organisations should evaluate their risk profile according to the evolving threat landscape and ensure coverage not only for financially motivated attacks but also for hacktivism and nation-state attacks.

2.        AI’s role in cybersecurity will evolve, for good and bad

Since ChatGPT’s launch in October 2022, there have been concerns worldwide regarding its potential to democratise cybercrime. Despite having guardrails to prevent malicious applications, a few creative prompts can get ChatGPT to generate near flawless phishing emails that sound “weirdly human” at immense scale. We’ve seen attackers use Gen AI in novel ways like deepfake and voice technology to scam banks out of millions. Companies adopting Gen AI must be wary about the vulnerabilities of model poisoning, data leakage, prompt injection attacks, etc. Attackers will continue to exploit innovation gaps with the increased use of Gen AI for legitimate use cases.

Hence, one of the AI Cybersecurity trends expected in 2024 is the maturation on how organisations protect enterprise-level use of Gen AI. This involves making sure that security controls, vulnerability management and threat monitoring activities are embedded through the entire lifecycle of AI development projects. Gen AI will further embed itself into cybersecurity capabilities. Its ability to summarise, weed through noise, and give concise summaries of security events is far greater than a human analyst’s (especially at the scale a modern SOC operates). With LLMs getting better by the day, we are bound to see more sophisticated applications that move beyond just being a clever and occasionally-hallucinating chatbot.

3.        Operational technology will remain the low-hanging fruit

Operational Technology is the heart of any industrial organisation. As the primary generator of revenue, OT systems must have a high level of cyber maturity. Palo Alto Networks’ State of Cybersecurity survey found that 67% of Indian government/essential services witnessed more than 50% increase in disruptive cyberattacks in 2022–2023. As organisations scramble to resolve OT-related cybersecurity woes, they will face a lack of specialised solutions that cater to the specific and niche needs of OT professionals. Many organisations still believe OT environments are protected by an air gap, whereas IT/OT convergence has resulted in OT being more connected than ever to IT and, in many cases, to the cloud. This has expanded the attack surface and greatly increased the risk to OT networks, without the investment in cyber controls.

A breach of OT systems can not only result in lost revenue, but also potentially, injuries or loss of life. A cyber secure OT environment is also a safe and reliable OT environment. A Zero Trust architecture will protect the most critical OT systems from threats, while allowing organisations to focus on their digital transformation. 2024 will see organisations invest in OT cyber security maturity to protect their most important business systems and manage the increased risk to an acceptable level.

4.        Consolidation to enable the next frontier in cybersecurity

Unit 42’s Cloud Threat Report (Volume 7) found that on average, security teams take approximately 6 days to resolve a security alert, with 60% of organisations taking longer than 4 days. In a threat landscape where attackers only require a few hours to find and exploit vulnerabilities, 4-6 days is just way too long. Organisations with disparate security tools that are not well integrated have a harder time deploying automation and orchestration. This is a major setback to reducing the mean time to detect and the mean time to respond. 

In addition to the lacklustre threat response, organisations with siloed solutions are having a hard time securing their rapid digital transformation initiatives. Alongside macroeconomic headwinds and workforce challenges, enterprises are looking to consolidate their vendor spread and reduce complexities. Put simply, it is easier to manage the cybersecurity stack if there is one point of contact when a crisis inevitably strikes. Over the long term, it reduces costs and yields better results. This is thanks to the increased visibility and seamless integration that comes with a unified security offering. More organisations are waking up to these benefits and thus 2024 will see customers focus on reducing complexities and turning to consolidated cybersecurity stacks. 

5.        Securing the cloud will be high on the agenda 

Per the State of Cybersecurity survey, India leads APAC in cloud migration, with 80% of businesses already having a large proportion of infrastructure on the cloud, and 42% adjusting their cybersecurity strategy to adopt cloud security. Early adopters of cloud typically start with a single hyperscaler. Naturally, the single cloud model would adopt native security tools from their chosen Cloud Service Provider (CSP). Through the course of time, they experience issues and outages that can only be addressed by adopting a multi or hybrid cloud strategy. This multicloud journey would most likely necessitate a review on their existing cloud security paradigm as native CSP security tools do not seamlessly translate to different CSPs. 

In 2024, organisations that have to contend with multi or hybrid cloud projects would move to establishing a more unified approach to security when dealing with more than one cloud provider. Rationalising cloud security tools across the entire development lifecycle will also be a focus as this provides much higher visibility, correlation, and security monitoring.

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Atlassian Corporation, the makers of team collaboration and productivity software including Jira Software, Confluence and Jira Service Management, has announced the general availability of Atlassian Intelligence, its new Generative AI-driven virtual teammate that accelerates teamwork through human-AI collaboration; at ‘Unleash’, its Agile and DevOps focused event. 

The company, in April, announced its ambition to transform teamwork by leveraging AI along with 20 years of data on how millions of software, IT, and business teams plan, track, and deliver work. Since then, 10% of Atlassian’s 265,000+ customers (over 20,000 customers) have been using their AI capabilities in beta. The company said that many are already reporting significant benefits, time savings, and productivity gains. 

Anutthara Bharadwaj, President, Atlassian said, “We’re excited to announce the first wave of Atlassian Intelligence capabilities that are generally available across our Cloud Platform. We believe the future of teamwork will be a partnership between humans and AI, wherever work gets done. As Atlassian Intelligence leverages the information in Jira and Confluence, the benefits you get from AI is more relevant to your unique needs, so everyone can more effectively do their best work by driving speed, efficiency, and excellence.” 

“We are building towards a future where virtual teammates will be the new workflow agent that will help teams sprint from ideas to action at an unprecedented pace,” she added. 

With Atlassian Intelligence, team members can draft pages of business-critical content in seconds, automate routine tasks by simply asking in plain natural language, and summarize long-winded content instantly using AI. 

In the coming future, Atlassian also plans to deploy the Bitbucket code review assistant which will help users review pull request diffs and leave comments automatically with suggested changes, so reviewers spend less time reviewing syntax and code conventions and more time reviewing critical changes. Software developers will also be able to auto-generate PR descriptions from commit messages, providing valuable context to the changes. 

In building, deploying and using Atlassian Intelligence, Atlassian is guided by its Responsible Technology Principles, which focus on transparency, trust, accountability, human-centricity, and teamwork. These principles help the company to take accountability for considering and using technologies like AI responsibly and in line with their values. The company recently launched its Responsible Technology Review Template, a guide to support companies in developing responsible AI and technology practices. 

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