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Automation use cases like intelligent document processing and communications mining could help organisations fast-track artificial intelligence operationalisation in 2024, according to a report from UiPath, as businesses seek to combine AI with automation to Strengthen processes.

Mark Fioretto, area vice president and managing director at AI-powered automation software company UiPath, said 2024 would see businesses in the Australasian region taking advantage of technologies in the traditional automation space but using AI to supercharge their results.

UiPath also predicts automation will drive process improvements in a number of areas together with AI, including improving AI safety processes by keeping humans in the loop and enabling environmental, social and governance data capture and reporting to be streamlined.

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C-suite sees operationalisation of AI as leading priority for 2024

The drive to commercialise generative AI capabilities inside products or processes inside organisations is the biggest AI trend UiPath is seeing among Australia’s C-level executives.

This comes as organisations struggle to adopt AI across their enterprises. A global report from McKinsey, for example, found almost half of organisations (45%) have no AI at scale (Figure A).

Fioretto said operationalisation required businesses to put AI-sourced information into practice,  which was likely to increase the market’s embrace of AI and automation combinations in 2024.

SEE: How Australia is adapting fast to a generative AI World.

“The C-suite really wants to operationalise AI and drive productivity in different ways within their organisations, as well as servicing customers in an improved manner,” Fioretto said. “This is making the combination of AI and automation really top of mind in C-suites right now.”

AI-powered automation to deliver productivity advantages

A global UiPath-commissioned survey of 200 companies, conducted by Bain & Company, found 70% of executives think AI-driven automation — combining both AI and automation components — would be “very important” or “critical” in fulfilling their business’ strategic objectives.

Most executives (85%) singled out higher productivity and efficiency as the primary advantages. McKinsey’s research estimates that, when generative AI is combined with other technologies, work automation could boost annual productivity growth by 0.2 to 3.3 percentage points.

“Having generative AI available in a more consumable way for the broader market means we are now seeing a combination of generative AI with specialised AI as customers adapt or use generative AI and different commercial models to commercialise AI inside processes,” Fioretto said.

Multiple AI and automation combinations are expected to rise

With executives seeking to implement use cases that can quickly generate value from AI, UiPath expects an uptick in Australian companies using AI and automation opportunities in 2024.

Intelligent document processing

UiPath singles out intelligent document processing as a key use case. IDP allows industries using lots of documents, such as the banking, healthcare, insurance and legal sectors, to Strengthen their speed, capacity and costs.

“IDP is a great example of creating a huge amount of efficiency combining generative AI and specialist AI with automation,” Fioretto said.

For example, Heritage Bank’s 2017 commitment to go digital and scale back- and middle-office processes has led to 90% process automation in some areas, including the compiling of living expense reports for loan applications. The bank, which is a UiPath customer, has also achieved a 98% accuracy in machine learning across its banking and wealth management businesses.

Communications mining

AI and automation can be paired to help organisations understand and act on emails, texts and unstructured data. For example, many organisations have contact centres with general or unmanned inboxes for inquiries, which need to be categorised and routed to the right person.

SEE: Australia’s telcos are deploying generative AI to Strengthen productivity.

“You are able to take the logic generated by large language models and through available information in the marketplace, but then, you are using specialised AI to route or enable the processing of the customer request efficiently within an organisation,” Fioretto said.

Automating automation

The natural language processing power of AI will “automate automation.” In the coming year, UiPath said developers and business users will increasingly ask their automation platform to build automations using natural language or no-code inputs. The platforms will be able to convert these prompts into real workflows, test cases, process mining and individual tasks.

AI safety success will lean on practical automation capabilities

The push to enhance AI safety will continue during 2024, according to UiPath, as the market seeks to mitigate the potential for misuse and miscalculation in the use of the technology. Fioretto said this will require guardrails and controls, supported by automation capabilities.

Human in the loop

Organisations are likely to expand “human in the loop” capabilities through “exception tagging,” which creates automated notifications if a process is not followed by flagging it as an exception. Humans can either be brought into the loop, or a reason can be captured for the exception.

Task mining

Task mining can be used to unearth or identify processes that are aged or not constructed correctly. This can create a “hidden floor” ensuring problem processes can be identified for discussion and uplifting the way AI governance processes or policies will be applied.

ESG reporting another application for AI-powered automation

The requirement for Australian organisations to report under new ESG standards from the International Sustainability Standards Board beginning on July 1, 2024, could drive further use of AI-powered data and reporting automations within organisations.

SEE: Explore the benefits of applying ESG standards to business processes.

Fioretto said new sustainability-related disclosures would require the collection, compilation, validation and reporting of ESG data across complex organisations, including supply chains, in an environment where managing this ESG data collection process is proving challenging.

AI-powered automation could help monitor metrics like carbon emissions, streamline data collection, processing, analysis and reporting, and reduce the likelihood of mistakes. Data could also be extracted, interpreted and processed from structured and unstructured documents.

AI and automation to redefine work as we know it

A exact report from the Australian Computer Society found that up to 90% of workers could be affected by artificial intelligence. UiPath expects 2024 to be characterised by a growing understanding of how humans will work collaboratively together with machines in the future.

“If I go back in time and think about when the internet was made usable and accessible to the general public, no one would have guessed the impact that was going to have in our work lives over time, or the way we interacted with each other,” Fioretto said. “We are in a similar situation now in terms of how AI will coexist with how we operate as humans.

SEE: AI is ranked one of the most important technologies for 2024, says IEEE.

“Over time, we will see an evolution in how it gets applied to how we work, but I think AI will be embedded in the way we interact with each other on a personal level and business level.”

Automation and AI will augment our human capacities

AI and automation is not about replacing humans, Fioretto said, but augmenting our capacities with data from the internet and other models. Human logic will still need to be applied to ensure AI models are responsible and fit within the parameters of how we interact with each other.

“Take no-code or low-code applications and technology and how they will apply in the workplace — the opportunity is enormous, not just in terms of efficiency but in creating a more satisfying time at work, where we are more focused on high value tasks,” Fioretto said.

For most of its 48 years, Microsoft has been known as the tech industry’s most effective fast-follower — a company that perfected inventions made elsewhere, rather than coming up with its own.

But this week has brought something different, according to Barry Briggs, a former chief technology officer at the US company: Microsoft has become the first in the industry to make the technology behind ChatGPT available as a standard feature in a widely used software product, potentially transforming the working lives of millions.

After nearly a year of soaring hopes for generative AI, the software industry will be watching the outcome for signs of whether the technology is ready to move from hype to business reality. Microsoft’s move will also be the first test of companies’ willingness to pay a high price for a technology that draws heavily on expensive computing resources such as the advanced chips needed to train AI models, and that make it costly to deliver.

On Wednesday, Microsoft officially declared “general availability” of a generative AI assistant, dubbed Copilot, in enterprise versions of its widely used Microsoft 365 suite of productivity apps, which includes Word, PowerPoint and Excel.

The move potentially puts new AI tools at the fingertips of an estimated 150mn workers, according to analysts, and helping them automatically generate documents and emails or create spreadsheets more easily. The software is designed to make it simple to draw on all the data a company holds in its Microsoft applications. Eventually, connections to other data stores are meant to make Copilot a “smart” front end for working with all of a company’s most valuable data.

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To judge from the price tag, Microsoft expects the technology to mark a profound advance in the everyday software applications used by many white-collar workers. The Copilot feature has been priced at $30 a month per user and is available as an upgrade to customers who already pay for the E3 or E5 editions of the company’s productivity apps. These cost $36 and $57 a month, respectively — meaning that the upgrade will add as much as 83 per cent to the monthly software bill.

“At that price point customers are going to be reluctant to adopt it enterprise-wide straight away,” said Derrick Wood, an analyst at TD Cowen. Instead, he added, they are likely to test it carefully before rolling it out, searching for the particular types of work that benefit the most from the technology. 

Despite this, the sheer number of workers who use its software and its early lead in generative AI has put Microsoft in pole position as the fast-evolving technology makes it into everyday use.

At a exact Gartner event attended by 9,000 corporate chief information officers and others, Microsoft’s AI dominated much of the conversation, said Jason Wong, an analyst at the IT research firm. One early sign of that came last week with an unexpected pick-up in growth at Microsoft’s Azure cloud platform, which the company attributed to AI.

“Microsoft has done well to generate mind share,” said Wong. “But it is not market share yet.” Other software companies “will be watching very closely” to see if it can turn the promise into real revenue gains, he added.

Unlike a normal product launch, there is much about the arrival of generative AI in mass-market software that looks experimental. It is not yet clear what types of work will benefit most from the technology or how easily workers will take to the new tools, analysts say.

There are also “risks of errors and misinterpretations and misuse”, said JP Gownder, an analyst at Forrester Research. A lazy worker, for instance, might send an AI-generated email without checking it for accuracy, or rely on an automated recap of a meeting without checking with one of the humans who was there to pick up nuances the AI failed to grasp. If AI makes it easier to produce more emails, it may add to the overload felt by many workers who are already drowning in electronic communications.

Microsoft executives admit there are many things they do not know about how workers will use the new technology or what unexpected side effects it may have.

“Certainly we’re in the early innings and we’re just learning,” said Jared Spataro, the Microsoft corporate vice-president in charge of bringing new features to its business applications. “I’m sure there are things we’re not thinking about right now.” But he predicted that positive surprises would outweigh the negative ones as the versatility of generative AI brings new and unexpected uses.

Spataro added that Microsoft has already collected enough data from its trials to show the new Copilot delivers big productivity gains. It plans to disclose the findings at its annual Ignite conference on November 14.

Besides measuring the time workers save by doing tasks such as automatically generating text and analysing numbers, Microsoft says its tests have included running control groups to validate the findings and developing ways to measure the quality of the generative AI output, rather than just its quantity.

Until customers see the results and get a chance to validate them with their own tests, however, such claims have to be taken on trust. “Right now, there aren’t a lot of facts,” said Wong. “Companies are either investing on faith, or fear: fear they’ll fall behind.”

The $30 a month figure was set after researching what customers would be prepared to pay for the sort of assistance the AI can deliver, said Spataro. Microsoft also looked at the “cost-per-head math” — how much $30 a month represented in terms of the overall cost of hiring a knowledge worker, and what kind of productivity gains would be needed to justify the extra software cost.

Gownder at Forrester calculated that the extra spending would be justified even with “pretty modest assumptions”, for instance assuming the software saved a high-priced worker as little as two hours a month.

Despite making big claims for the AI, Microsoft executives have sought to lower expectations about its revenue impact in the short term, and Wall Street forecasts are tempered. Even a successful rollout of the technology might only add 1 per cent to Microsoft’s revenue growth in its 2025 fiscal year, which starts next July, calculated TD Cowen analyst Wood. That is the equivalent to about $2-2.5bn, Wood added.

Competition with other software companies could also limit the potential. The APIs offered by OpenAI and other makers of large language models, which make it easy for programs to tap into their services, have opened the way for generative AI to become a standard feature of many software applications.

Microsoft will still have a number of advantages over other companies, said Wood, such as being able to tap into data held in Microsoft applications and its close relationship with OpenAI. But it is not clear how much of a premium it will be able to command if automatically generating emails or summarising documents become routine activities available from many different applications. “We’ll see if Microsoft can hold these price points,” he added.

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Microsoft is rolling out an array of major changes to its software engineering process aimed at improving the security of its widely used platforms, the company announced Thursday.

In a pair of blog posts, top executives from the tech giant outlined updates that are meant to enable its software to be secure by default while also improving key areas such as identity security and cloud vulnerability mitigation.

The changes are a part of Microsoft’s newly announced Secure Future Initiative, the company said.

While the new initiative also aims to use AI in a bigger way to address evolving cyberthreats, the changes around Microsoft’s software engineering will potentially impact the company’s largest platforms including Azure, Windows and Office 365.

The changes come just a few months after a high-profile Microsoft cloud breach that impacted US government email accounts, and prompted an inquiry into Microsoft’s security practices by US Senator Ron Wyden.

Separately, industry executives including Tenable chief executive Amit Yoran have recently accused Microsoft of responding slowly and inadequately to vulnerability disclosures.

And federal cybersecurity officials such as CISA Director Jen Easterly have slammed Microsoft’s monthly “Patch Tuesday” software release, which typically reveals scores of vulnerabilities, saying it represents the opposite of a “secure by default” approach to software development.

"New standard for security"

In one of the blog posts announcing the changes this week, Microsoft president Brad Smith wrote that its new initiative will “bring together every part of Microsoft to advance cybersecurity protection.”

The initiative will set “a new standard for security” at Microsoft through evolving “the way we design, build, test, and operate our technology,” Smith said.

In the second post, Microsoft’s top security executive Charlie Bell wrote that “a more secure future will require new advances in fundamental software engineering.”

Notably, Bell’s blog post references Bill Gates’ famous 2002 memo on “Trustworthy Computing,” in which Gates committed Microsoft to bringing a stronger focus on the security of its products.

Bell included one of Gates’ lines from the memo: “if we don’t do this, people simply won’t be willing — or able — to take advantage of all the other great work we do.”

For Microsoft, Bell wrote, that notion “still holds true over two decades later.”

Enabling "Secure By Default" software development

Microsoft’s software development lifecycle (SDL) approach, Smith wrote, is now going to evolve into what the company is calling “dynamic SDL.”

The new approach — which will be powered in part by increased usage of automation and AI — will “continuously integrate cybersecurity protection against emerging threat patterns as our engineers code, test, deploy, and operate our systems and services,” he wrote.

Bell wrote that AI-powered “dynamic SDL” will enable Microsoft to “deliver software that is secure by design, by default, and in deployment.”

“Our goal is to accelerate the deployment of CodeQL integrated with GitHub Copilot learnings,” Bell wrote, referring to Microsoft-owned GitHub’s generative AI coding assistant tool.

“Principles like the Security Development Lifecycle will continue to guide our software supply chain, while we expand automation and build with memory safe languages,” Bell wrote.

“We will also use threat modelling and Code QL as complementary techniques to identify and mitigate security risks and vulnerabilities in our products and services."

"We will use Code QL to perform static and dynamic code analysis, helping our teams find and fix bugs in our code at AI speed and scale.”

Microsoft does still plan to keep SDL “front and center,” but the company will “continue expanding [its] use of memory safe languages (MSLs) in our products whenever possible, so that we keep building security in at the language level, helping to eliminate classes of traditional software vulnerabilities.”

Expansion of default MFA settings

Another update from Microsoft is that the company plans to “enable customers with more secure default settings for Multi-Factor Authentication (MFA) out-of-the-box.”

This expansion — which will take place “over the next year” — will bring Microsoft’s “current default policies to a wider band of customer services,” Smith (pictured) wrote.

In his post, Bell said that Microsoft has concluded that when it comes to MFA, which is considered more secure than typical password-only authentication, the practice “must scale where our customers need them most to provide protection.”

“Over the past year, we have learned a great deal from customers in the process of making MFA on by default for new customers, for example,” he wrote.

“To continue the identity example - those learnings and communications with customers helped pave the way for our introduction of wider MFA default policies for wider bands of customer tenants."

"By focusing on communications as well as engineering - explaining where we were focused on defaults and how customers benefit – we achieved more durable security for our customers.”

Additionally, Bell noted that MFA “is just one area of defaults for us” — adding that “over the next year you will see us accelerate security defaults.”

Faster cloud vulnerability mitigation

As part of the new security initiative announced Thursday, Microsoft will be “pushing the envelope in vulnerability response and security updates for our cloud platforms,” Smith wrote in his blog post.

Notably, Microsoft plans to “cut the time it takes to mitigate cloud vulnerabilities by 50 per cent,” he wrote.

The company also plans to “take new steps to ensure more transparent reporting by Microsoft and will encourage more transparent reporting in a more consistent manner across the tech sector,” he wrote.

Bell added in his post that “we are in a position to achieve this because of our investment and learnings in automation, orchestration, and intelligence-driven tools and processes.”

Improved identity protection

Microsoft executives said in the announcements this week that it will “strengthen” the identity protection capabilities in its products, amid the surge in identity-based attacks.

Bell described the move as Microsoft adopting a “new identity system.”

The new system, he wrote, “will provide a unified and consistent way of managing and verifying the identities and access rights of our users, devices, and services, across all our products and platforms.”

Microsoft also plans to “make these advanced capabilities freely available to non-Microsoft application developers,” Smith wrote in his blog post.

Confidential computing migration

As part of boosting its identity security, Microsoft will also move its identity platforms into confidential computing infrastructure.

Confidential computing provides hardware-based isolation of data while it’s in use, reducing the risk of compromise due to the decryption of data for usage.

“In this architecture, data governing identities is encrypted not only at rest and transit but during computational processes as well,” Bell wrote in his post.

“This means that even if an attacker gets through our layered defenses in the course of targeting encryption keys, the key data is designed to be inaccessible within automated systems that do not require human touch.”