Artificial Intelligence AI

The Latest

1 March 2022. Microsoft recently launched Carbon Call with ClimateWorks Foundation and more than 20 other leading organisations in the private, philanthropic, scientific and non-governmental sectors to develop more reliable and interoperable carbon emissions accounting practices. The collaboration is expected to address and solve gaps in current global carbon accounting systems, with a focus on carbon removal and land sector, methane, and indirect emissions. 

Why it’s Important

There has been a noticeable growth in the number of hyperscale Cloud vendors publicising their efforts to reduce their carbon footprint and energy consumption levels. Such growth outnumbers the total of on-premise data centre services that are following the same move towards carbon-free energy sources and more sustainable ICT operations.

This reflects the industry’s answer to the immediate call for action on climate change and the economic advantages of hyperscale. However, global standards for sustainability reporting still vary widely, according to a study published by the International Federation of Accountants and the Association of International Certified Professional Accountants. The lack of a robust set of sustainability-related reporting standards presupposes that any vendor may overstate its claims of adhering to a climate-first approach, further relegating corporate reporting across a range of environmental, social and governance (ESG) areas into suspicion.

But progress has been made since. In November, during the 2021 UN Climate Change Conference (COP26), the International Financial Reporting Standards Foundation proposed the International Sustainability Standards Board (ISSB) to bring the much needed transparency in reporting across different industries, enterprises and regions.

Microsoft's adoption of an emerging global standard for reporting reflects the next stage of the trend towards ICT sustainability issues. By 2025, IBRS expects that not only all the hyperscale Cloud vendors will have adopted a standardised carbon report, but most of the top Fortune 500 companies will be following suit. Around this time, it is expected that public sector shared services will be put under greater scrutiny to do the same move towards carbon-free energy sources with a globally agreed set of standards.

Who’s impacted

  • COO, CIO, CTO
  • Data centre managers
  • Corporate risk and policy directors
  • Sustainability managers

What’s Next?

Organisations must learn to start monitoring trends in sustainable computing, especially among the hyperscale Cloud vendors. As all organisations will soon be obliged to adhere to a consistent, harmonised and global set of sustainability reporting standards that will help define collective enterprise reporting and accountability, be prepared for boards to request standardised ICT sustainability reporting. This will enhance their commitment to actively participating in collecting and reporting sustainability information and the credibility of their report. 

Finally, organisations must consider what solutions may be needed to integrate ESG in creating value for the organisation over the long term, rather than attempting to build such capabilities in-house with existing analytics platforms. 

Related IBRS Advisory

  1. VENDORiQ: Cloud Vendors will Push New Wave of Sustainable ICT Strategies
  2. VENDORiQ: Oracle Announces Innovation Lab During COP26 Summit

The Latest

22 February 2022: Process intelligence and automation company Nintex announced its acquisition of robotic process automation (RPA) developer Kryon. Australian low-code vendor Nintex, plans to improve its intelligent process automation (IPA) features through Kryon’s process discovery technology capabilities and full cycle RPA with artificial intelligence (AI).

As a process management and automation software builder, Nintex offers low-code design platforms for IT teams, operations experts and business analysts. Some of its largest clients in Australia include Naylor Love, Toyota Australia, Arab Bank Australia, RICOH, Auswide Bank, Port Stephens Council in New South Wales, Auto & General Holdings, and Allegis Group who have benefitted from its low-code development tools to help employees, regardless of their programming expertise, create applications that solve unique enterprise challenges.

Why it’s Important

Nintex’s move to acquire Kryon is yet another example of the merging of all low-code tools (i.e., process singularity) and how mid-tier low-code vendors are pushing up the low-code spectrum. This broad ecosystem of solutions, each with unique traits and features that fit specific organisational structures, should have specific modern low-code platforms that match an organisation’s ecosystem to help better streamline operational processes. In addition, constantly ensuring governance features to avoid the chaos that can ensue from unfettered development when acquiring low-code platforms is crucial in the long-term for better return on investment (ROI) whatever low-code solution is selected.

Nintex is also one of the many Australian companies that have exhibited fast-growing performances in the international market recently through acquisitions and mergers. However, as previously noted by IBRS, most local enterprises and the national government have lower regard for smaller Australian vendors making a name abroad. In many cases, smaller local vendors offer better value and generally have positive project outcomes as a result of their vested interest in meeting their clients’ expectations.

Who’s impacted

  • COO, CIO, CTO
  • Business analysts

What’s Next?

IBRS recently conducted a market scan on low-code vendor trends and found out that large vendors will continue acquiring today’s most successful low-code platform companies until 2025. This will help expand their product portfolios to secure a majority of market share. In this regard, when looking at low-code platforms, organisations must consider the greater ecosystem of low-code tools that will meet their long-term needs. For instance, vendors that can offer a more robust platform that caters to internet of things (IoT) solutions can help organisations focus on IoT devices and controllers instead of hardware and software development integrations.

Related IBRS Advisory

  1. Low-Code Mythbusting
  2. Hammering Low-Code into Place Takes Time
  3. Low-Code Platform Feature Checklist
  4. VENDORiQ: What Marketplacer Shows Us About Buying Aussie Tech

The Latest

25 January 2022: ServiceNow has recently launched ServiceNow Impact that provides AI-driven recommendations along with human-powered solutions on technical support, prescriptive guidance, preventive solutions, role-based training, curated content, and coaching using the Now Platform. Users will receive personalised recommendations on customer success, progress monitoring, platform architecture and performance management to improve their overall workflow automation.

ServiceNow’s AI is leveraged to deliver recommendations that allow users to optimise their existing ServiceNow platform, without integrating third party tools into the system. The solution also provides personal support through on-demand training, and dedicated expert teams and developer consulting depending on a user’s subscription package. 

Why it’s Important.

IBRS has observed a rise in the number of AI decision support services being integrated into workflow automation tools. Hyper-automation on decision-making processes built on top of existing workflow platforms and enterprise resource planning (ERP) solutions is where most organisations will obtain the quickest impact from AI - specifically machine learning (ML). Therefore, instead of investing in separate ML tools and developing custom algorithms, it may be more prudent to leverage existing SaaS platforms emerging AI and ML capabilities.

In addition, many service providers that use AI to automate workplace processes, customer journey flows and enterprise spend management continue to expand their tool’s capabilities in terms of customised solutions to address each organisation’s requirements on value acceleration. In this regard, AI will continue to maintain its essential ‘invisible’ role by recommending better workflows, which in turn drive service quality and agility.

Who’s impacted

  • CIO
  • System administrators
  • Development team leads
  • Business analysts

What’s Next?

Look for opportunities to leverage AI (and ML) from existing investments in SaaS platforms. In particular, look for how AI is being used to make recommendations on improving workflow with low-code development platforms. Bespoke AI initiatives will be less utilised in favour of AI being added to already existing SaaS applications.

Related IBRS Advisory

  1. Machine Learning Operations (MLOps), the AI Productivity Fast Track
  2. Trends for 2021-2026: No new normal and preparing for the fourth-wave of ICT
  3. How can AI reimagine your business processes?
  4. VENDORiQ: ServiceNow to Acquire RPA Vendor Intellibot

The Latest

18 August 2021: While natural language processing AIs are becoming increasingly accurate in how they respond to questions, their ability to explain how they arrived at their answers has been limited. As The Doctor reveals, confronting a rogue AI in the Green Death, ‘Why?’ remains, perhaps, the hardest question for machine intelligence. IBM’s AI Horizons Network is developing a method to enable AIs to explain their reasoning with a common sense data set.1 

Why it’s Important.

Today, virtual service agents, both customer facing and internal IT held-desks, are effective and very efficient FAQs. They can identify a context from natural language and then provide answers to questions, as well as provide follow up answers based on the original context. However, they cannot provide details as to how they arrived at any given answer, which generally leads to a request for human manual intervention.

Specialists who develop conversation virtual service agents, work around these limitations by programmatically refining the answers AIs have available (i.e. curating the FAQ) to include reasons. E.g. “Your transaction has been declined because of XYZ.” 

IBMs work to allow AIs to report back on their reasons, may not only minimise the programming effort needed to develop virtual agents, but allow them to report decision-making in ways that organisations have not considered. 

While AI development will remain a niche activity for most Australian organisations, AI will increasingly find its way into enterprise SaaS products. Natural language AIs coupled with machine learning over knowledge assets held in core enterprise systems will see a rapid increase in the use of virtual agents, both for internal and external services. 

Who’s impacted

  • AI specialists
  • Service automation / customer experience teams
  • ICT strategy leads

What’s Next?

The rapid improvements in AI quality, coupled with their integration into most enterprise SaaS products, will make them ubiquitous for customer service delivery within the next 2-5 years.

Organisations need to start exploring the AI service agent capabilities already available in their SaaS products, and develop plans for how to leverage such capabilities. The goal should not be to deliver an ‘all-singing and dancing’ virtual agent experience, but rather to incrementally introduce capabilities over time, learning how clients and staff wish to interact, and continually leveraging advances in technology as they become available. 

Related IBRS Advisory

  1. Chatbots Part 1: Start creating capabilities with a super-low-cost experiment
  2. Preparing for the shift from digital to AI-enabled transformation
  3. BMC Adds AI to IT Operations
  4. Trends for 2021-2026: No new normal and preparing for the fourth-wave of ICT
  5. Software Agents Maturity Model
  6. Artificial intelligence Part 2: Deriving business principles

 

Footnotes

1. COMMONSENSEQA: A Question Answering Challenge Targeting Commonsense Knowledge, 2019 Association for Computational Linguistics

The Latest: 

26 June 2021: Zoho briefed IBRS on Zoho DataPrep, it’s new business-user focused data preparation which is being included in its existing Zoho Analytics tool, as well as being available separately as a tool to clean, transform and migrate data. DataPrep is in beta, and will be officially launched on 13th July 2021.

Why it’s Important

Traditionally, cleaning and transforming data for use in analytics platforms has involved scripting and complex ETL (extract, transform and load) processes. This was a barrier to allowing business stakeholders to take advantage of analytics. However, several analytics vendors (most notably Microsoft, Tableau, Qlik, Snowflake, Domo, etc.) have pioneered powerful, drag-and-drop low-code ETL into their products.  

Zoho, which is better known for its CRM, has an existing data analytics platform with Cloud storage, visualisation and reports, and dashboards. While the product is not as sophisticated as its top-drawer rivals, it can be considered ‘good enough’ for many business user’s needs. Most significantly, Zoho Analytics benefits from attractive licensing, including the ability to share reports and interactive dashboards both within an organisation and externally. 

However, Zoho Analytics lacked a business-user-friendly, low-code ELT environment, instead relying on SQL scripting. Zoho DataPrep fills this gap by providing a dedicated, AI-enabled platform for extracting data from a variety of sources, allowing data cleaning and transformations to be applied, with results being pushed into another database, data warehouse and Zoho Analytics. 

All existing Zoho Analytics clients will receive Zoho DataPrep with no change to licensing.

However, what is interesting here is Zoho’s decision to offer its DataPrep platform independent of its Analytics platform. This allows business stakeholders to use the platform as a tool to solve migration and data cleaning, not just analytics. 

IBRS’s initial tests of Zoho DataPrep suggest that it has some way to go before it can compete with the ready-made integration capabilities of Tableau, Power BI, Qlik, and others. In addition, it offers less complex ETL than it’s better established rivals. But, that may not be an issue for organisations where staff have limited data literacy maturity, or where analytics requirements are relatively straightforward.

Who’s impacted

  • CIO
  • Development team leads
  • Business analysts

What’s Next?

The bigger take out from Zoho’s announcement is that ETL, along with all other aspects of business intelligence and analytics, will be both low-code, business-user friendly and reside in the Cloud. ICT departments seeking to create ‘best of breed’ business intelligence architectures that demand highly specialised skills will simply be bypassed, due to their lack of agility. While there will be a role for highly skilled statisticians, data scientists, and machine learning professionals, the days of needing ICT staff that specialise in specific reporting and data warehousing products is passing. 

Related IBRS Advisory

  1. Snowflake Gets PROTECTED Status Security Tick by Aussie Auditor
  2. IBRSiQ: Power BI vs Tableau
  3. Business-First Data Analytics
  4. AWS Accelerates Cloud Analytics with Custom Hardware
  5. IBRSiQ AIS and Power BI Initiatives
  6. Trends in Data Catalogues
  7. When Does Power BI Deliver Power to the People?
  8. Staff need data literacy – Here’s how to help them get it

The Latest

19 May 2021: Google has launched Vertex AI, a platform that strives to accelerate the development of machine learning models (aka, algorithms). According to Google and IBRS discussions with early adopters, the platform does indeed dramatically reduce the amount of manual coding needed to develop (aka, train) machine learning models. 

Why it’s Important

The use of machine learning (ML) will have a dramatic impact on decision making support systems and automation over the next decade. For the majority of organisations, ML capabilities will be acquired as part of regular upgrades of enterprise SaaS solutions. Software leaders such as Microsoft, Salesforce, Adobe and even smaller ERP vendors such as Zoho and TechnologyOne, are all embedding ML powered services into their products today, and this will only accelerate.

However, developing proprietary ML models to meet specific needs may very well prove critically important for a few organisations. Recent examples of this include: customise direct customer outreach with specific language tailored to lessen overdue payment, and creating decision support solutions to reduce the occurrence of heatstroke.

IBRS has written extensively on ML development operations (MLOps). However, the future of this disciplin e will likely be AI-powered recommendation engines that aid data teams in the development of ML models. In a recent example, IBRS monitored a data scientist as they first developed an ML model to predict customer behaviour using traditional techniques, and then used a publicly available tool that leveraged ML itself to build, test and recommend the same model. Excluding data preparation, the hand-coded approach took 3 days to complete, while the assisted approach took several hours. But more importantly, the assisted approach tested more models that the data scientist could test manually, and delivered a model that was 3% more accurate than the hand-coded solution.

It should be noted that leveraging ‘low-code’ AI does not negate the need for data scientists or the pressing need to improve data literacy within most organisations. However, it has the potential to dramatically reduce the cost of developing and testing ML models, which lowers the financial risk for organisations experimenting with AI.

Who’s impacted

  • CIO
  • COO
  • CFO
  • Marketing leads
  • Development team leads

What’s Next?

Prepare for low-code AI to become increasingly common and the hype surrounding it to grow significant in the coming two years. However, the excitement for low-code ML should be tempered with the realisation that many of the use cases for ML will be embedded ‘out of the box’ in ERP, CRM, HCM, workforce management, and asset management SaaS solutions in the near future. Organisations should balance the ‘build it’ versus ‘wait for it’ decision when it comes to ML-power services. 

Related IBRS Advisory

  1. Six Critical Success Factors for Machine Learning Projects
  2. Options for Machine Learning-as-a-Service: The Big Four AIs Battle it Out
  3. How can AI reimagine your business processes?
  4. Low-Code Platform Feature Checklist
  5. VENDORiQ: BMC Adds AI to IT Operations
  6. Artificial intelligence Part 3: Preparing IT organisations for artificial intelligence deployment

The Latest

May 2021: Talend, a vendor of data and analytics tools, released its Data Health Survey Report that claims 36% of executives skip data when making decisions, and instead go “with their gut”. At the same time, the report claims that 64% of executives “work with data everyday”. On the surface, these two figures seem at odds. However, the report goes on to claim 78% of executives “have challenges in making data drive decisions”, and this is largely due to data quality issues. However, the most interesting finding from the report is “those who produce and those who analyse data live in alternative data realities”.

Why it’s Important

At its core, this report highlights the issue of data literacy. The report was compiled from 529 responses from companies with over USD10 million in sales. A quarter of respondents were from the Asia Pacific region. However, IBRS cautions drawing Australia-specific inference, given that different markets have differing levels of data literacy maturity. No details were given for industry, which is also likely to impact data literacy maturity. In fairness, any more detailed analysis of a country or industry would not be feasible, given the sample size. 

The above concerns aside, the report does highlight the importance of data literacy: investments in big data tools are useless unless executives are knowledgeable and well versed in the key concepts of applying analytical thinking to business decisions. IBRS notes that without data literacy, the most common use of new self-service visualisation tools such as Power BI, Looker, Domo, Tableau, Qlik, Zoho and others, is to ‘prove’ executives' gut feelings. In short, too often visualisations tools are used to reinforce the ‘current ways of thinking’ rather than seek areas for improvement.  

The report’s statement that “those who produce and those who analyse data live in alternative data realities”, frequently underpins IBRS inquiries into why business intelligence and analysis programs fail to produce the expected business benefits.

Who’s impacted

  • Business intelligence/analytics teams
  • Senior line-of-business executives
  • Human resources/training teams

What’s Next?

ICT teams responsible for providing business intelligence and analytics services need to cease solely focusing on the tools and technologies and ‘getting data curated’, and spend time exploring which business decisions would most benefit from the application of analytical thinking. However, the ICT teams cannot do this alone. They need to be involved in uplifting data literacy among line-of-business executives and work closely with them to identify the decisions that not only can be addressed with data, but those that would make the biggest difference to organisational outcomes. This does not mean that all aspects of a data scientists role need to be explained to business executives. Rather, training executives in the principles of using data to inquire into issues or disprove current ways of doing things is more important.  

Related IBRS Advisory

  1. Staff need data literacy – Here’s how to help them get it
  2. When Does Power BI Deliver Power to the People?
  3. The critical link between data literacy and customer experience

IBRS interviews Dr Kevin McIsaac, a data scientist who frequently works with board-level executives to identify and prototype powerful data-driven decision support solutions.

Dr McIsaac discusses why so may 'big data' efforts fail, the role ICT plays (or rather, should not play) and the business-first data mindset.

The Latest

29 April 2021: Cloud-based analytics platform vendor Snowflake has received ‘PROTECTED’ status under IRAP (Australian Information Security Registered Assessors Program).  

Why it’s Important

As IBRS has previously reported, Cloud-based analytics has reached a point in cost of operation and sophistication that it should be considered the de facto choice for future investments in reporting and analytics. However, IBRS does call out that there are sensitive data sets that need to be governed and secured to a higher standard. Often, such data sets are the reasons why organisations decide to keep their analytics on-premises, even if the cost analysis does not stack up against IaaS or SaaS solutions.

The irony here is that IT professionals now accept that even without PROTECTED status, Cloud infrastructure provides a higher security benchmark than most organisations on-premises environments.

However, security must not be overlooked in the analytics space. Data lakes and data warehouses are incredibly valuable targets, especially as they can hold private information that is then contextualised with other data sets.

By demonstrating IRAP certification, Snowflake effectively opens the door to working with Australian Government agencies. But it also signals that hyper-scale Cloud-based analytics platforms can not only offer a bigger bang for your buck, but greatly improve an organisation's security stance.

Who’s impacted

  • CDO
  • Data architecture teams
  • Business intelligence/analytics teams
  • CISO
  • Public sector tech strategists

What’s Next?

Review the security certifications and stance of any Cloud-based analytics tools in use, including those embedded with core business systems, and those that have crept into the organisations via shadow IT (we are looking at you, Microsoft PowerBI!). Match these against compliance requirements for the datasets being used and determine if remediation is required.

When planning for an upgraded analytics platform, put security certification front and centre, but also recognise that like any Cloud storage, the most likely security breach will occur from poor configuration or excess permissions.

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  4. VENDORiQ: Snowflakes New Services Flip The Analytics Model

The Latest

7 May 2021: Analytics vendor Qlik has released its mobile client Qlik Sense Mobile for SaaS. During the announcement, Qlik outlined how the new client enables both online and offline analytics and alerting. The goal is to bring data-driven decision-making to an ‘anywhere, anytime, any device’ model. 

Why it’s Important

While IBRS accepts that mobile decision support solutions will be of huge value to organisations, this needs to be tempered with an understanding that not all decisions should be made in all contexts. There is a very real danger that in the hype surrounding analytics, people will start making decisions in less than ideal contexts. Putting decision support algorithms (i.e. agents), KPI dashboards and simply modelling tools on mobile devices will likely be the next wave of analytics. In short, mobile big data/AI driven solutions that support specific, narrow mobile work tasks will be a very big deal in the near future.

However, creating and diving into data - that is, data exploration - is or should be, a process rooted in deep, careful, considered scientific thinking. That is a cognitive task that is not well suited to a mobile device experience. This is not just due to the form factor, but also the working context. Such deep thinking requires focus that a mobile work context does not provide.

As organisations embrace self-service analytics and more staff are engaged in creating and consuming visualisations and reports, data maturity will become an increasingly important consideration. However, data literacy is not just a set of skills to learn: it requires a change in culture and demands staff become familiar with rigorous models of thinking. It also requires honest reflection, both of the organisation’s activities and individually. 

While mobile analytics will be a growing area of interest, it will fail without a well-structured program to grow data literacy within the organisation and without granting staff the time and appropriate work spaces to reflect, explore and challenge their assumptions using data.

Who’s impacted

  • CDO
  • HR directors
  • Business intelligence groups

What’s Next?

Organisations should honestly assess staff data literacy maturity at a departmental and whole or organisation level. Armed with this information, a program to grow data literacy maturity can be developed. The deployment of data analytics tools, and indeed data sets, should coincide with the evolution of data literacy within the organisation. 

Related IBRS Advisory

  1. Staff need data literacy – Here’s how to help them get it
  2. When Does Power BI Deliver Power to the People?
  3. The critical link between data literacy and customer experience

The Latest

16 April 2021: BMC has released a new edition of its Helix Platform, which leverages machine learning algorithms to support AI-driven IT operations (AIOps) and AI-driven service management (AISM) capabilities. The introduction of these algorithmic features enable IT service and operations teams to predict and resolve issues more effectively.

Why it’s Important

The use of algorithms to both categorise and predict events in IT operations is a growing trend. Such AI capabilities will be increasingly embedded in existing IT operations suites. As vendors enter a new ‘AI-powered’ competitive phase, these new AI capabilities will be included as part of regular upgrades and maintenance, rather than as add-on components.

Getting value from the new AI capabilities requires planning very human responses.  

For example, the predictive capabilities of algorithms, especially when using multi-organisational data, can provide op teams with alerts well in advance of problems becoming apparent. But unless op teams are resourced and given budget to respond to such ‘predictive maintenance’ issues, these predictive capabilities will be relegated to little more than an alarm clock with a snooze button. 

Likewise, the ability to correctly leverage and continually train advisory from resolution support algorithms, will demand both training of, and input from, the support team. The algorithms are only as good as the information and the contexts they can draw on. Support team people play an intimate role in ensuring the right information is selected for training the algorithm and, most importantly, the right contexts. This is especially pertinent as virtual agents (chatbots) are introduced for self-help capabilities.

Who’s impacted

  • CIO
  • IT operations staff
  • Support desk

What’s Next?

Begin to track the new AI capabilities available in IT operations support platforms, not just for the platforms used by your organisation, but in the competitive landscape. While there is no critical priority to adopt AI-powered IT operations or service management capabilities (just yet), it is important to understand what is coming and what may already be available as part of your current licensing agreements.

Assemble a working group to explore how AI capabilities could positively impact IT operations and service management, and the changes in process and roles that would be required to leverage them.

In short, start planning for AI-powered operations and a service management future.

Related IBRS Advisory

  1. Running IT-as-a-Service Part 55: IBRS Infrastructure Maturity Model
  2. Sustaining efficiency gains demands architecture risks mitigation Part 2
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  4. IBRSiQ: Approach to identifying an ITSM SaaS Provider

The Latest

23 February 2021: The appetite for crowdfunding of tech startups looks to remain strong, with the fledgling accounting software vendor Thrive securing AU$3 million through the Birchal service.  

Why it’s Important

There are two lessons to take from this announcement. 

First, commercial crowdfunding is a growth area that will favour niche tech start-ups. As more success stories emerge, this has the potential to re-invigorate the Australian startup community, which has been lagging. 

Second, it highlights the likely capabilities to be introduced in SaaS-based financial solutions: namely AI-powered automation and machine-learning decision support.

Who’s impacted

  • CIO
  • CFOs
  • Individual investors

What’s Next?

There is the potential for larger organisations to set aside funds to invest in startups. CIOs and CFOs may wish to watch the crowdfunding space that may provide relevant solutions to their needs, or secure services that may complement or even compete with their organisation. While IBRS acknowledges this strategy will not be suitable for the majority of organisations it works with, there is the possibility this will become more common over the next decade, especially for startups in security, Cloud management and cost control, AI-powered automation and machine learning-based decision support systems.

While Thrive is unlikely to be of interest to CIOs, being targeting squarely at SMEs and sole traders, the vendor’s goals leverage AI to automate much of the account process and provide recommendations, highlighting where development dollars will be going for many SaaS-based accounting solutions.

Related IBRS Advisory

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The Latest

2 February 2021: Google has announced general availability of Dialogflow CX, it’s virtual agent (chatbot) technology for call centres.  The service is a platform to create and deploy virtual agents for public-facing customer services. Google has embraced low-code concepts to allow for rapid development of such virtual agents with a visual builder. The platform also allows for switching between conversational ‘contexts’, which allows for greater flexibility in how the agents can converse with people that have multiple, simultaneous customer service issues.

Why it’s Important

While virtual agents are relatively easy to develop over time, two key challenges have remained: 

  1. the ability to allow non-technical, customer service specialists to be directly involved in the creation and continual evolution of the virtual agents
  2. the capability of virtual agents to correctly react to humans’ non-linier conversational patterns.

Google’s Dialogflow CX has adopted aspects of low-code development to address the first challenge. The platform offers a visual builder and the way conversations are developed (contexts) can be described as ‘program by example’. While there are third-party virtual agent platforms that further simplify the development of agent workflows (many of which build on top of Dialogflow), the Google approach is proving sufficient for non-technical specialists to get heavily involved in the development and fine-tuning of virtual agents

Who’s impacted

  • CIO
  • Development team leads
  • Business analysts

What’s Next?

If not already in place, organisations should establish a group of technical and non-technical staff to explore where and how virtual agents can be used. Do not attempt a big bang approach: keep expectations small, be experimental and iterative. Leverage low-code ‘chatbot builder’ tools to simplify the creation of virtual agent workflows, while leveraging available hyperscale cloud platforms for the back end of the agents. 

Related IBRS Advisory

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  2. Virtual Service Desk Agent Critical Success Factors
  3. SNAPSHOT: The Chatbot Mantra: Experimental, experiential and iterative
  4. New generation IT service management tools Part 1
  5. Artificial intelligence Part 3: Preparing IT organisations for artificial intelligence deployment
  6. VENDORiQ: Tribal Sage chatbot

The Latest

5 December 2020: Australian education solution vendor Tribal, has upgraded its digital learning design chatbot. The move is illustrative of how chatbots can be leveraged to aid complex tasks - in this case, learning content, delivery, and leaner coaching.

Why it’s Important

Chatbots are not unique to Tribal. However, Tribal is demonstrating how such agents can deliver new capabilities into the LMS market, which can be glacial in the adoption of innovation. The Tribal chatbot is aimed at improving knowledge transfer inside an organisation. It assists domain experts to build learning content and share knowledge by recommending approaches to online training.

Who’s Impacted

  • CIO / CTO
  • Service delivery teams 

What’s Next?

Like most forms of AI, chatbots will make their way into organisations through their addition to existing software solutions, either via paid upgrades or as part of the ongoing improvements of SaaS solutions. Chatbots will increasingly act in an advisory manner or as a guide for complex processes inherent in the vendors’ solutions. 

As a result of this trend, staff will be presented with a growing number of chatbots embedded in different vendor’s solutions, each serving a specific purpose. This itself will present a new challenge for digital maturity and staff satisfaction.

Related IBRS Advisory

The Latest

2 December 2020: Salesforce Einstein is being extended into the Mulesoft automation and data integration platform. The newly announced Flow Orchestrator enabled non-technical staff to transform complex processes into industry-relevant events. The new AI-assisted MuleSoft Composer for Salesforce will allow an organisation to integrate data from multiple systems, including third-party solutions.

Why it’s Important

AI enables business process automation as a key technology enabler that favours organisations with a Cloud-first architecture. Salesforce will leverage its experience and connections with selling to organisation’s non-IT executives to secure a strong ‘brand leadership’ position in this space.

Who’s Impacted

  • CIOs
  • CTOs
  • CRM Leaders

What’s Next?

In mid-2019, IBRS noted a significant upswing in interest in Mulesoft and integration technologies more broadly from the non-ICT board-level executives. In particular, COOs and CFOs expressed strong interest in, and awareness of, process automation through APIs.  

Digging deeper, IBRS finds that Salesforce account teams, who are well-known for bypassing the CIO and targeting senior executive stakeholders, are also bringing Mulesoft into the business conversation. Also, Microsoft is expected to double-down on AI-enabled business process automation with the PowerPlatform. 

As a result, the addition of Salesforce Einstein AI into the discussion of automation and integration is expected to land very well with COOs and CFOs. 

CIOs need to be ready to have sophisticated discussions with these two roles regarding the potential for AI in process automation. Expectations will be high. Understanding the possible challenges of implementing such a system takes careful consideration. CIOs should be ready to build a business case for AI-enabled business process automation.

Related IBRS Advisory

IBRS was asked to present on the AI market for 2018 - 2019. This advisory presents an AI market overview for this time with an outlook towards 2025. How has your organisation's AI journey progressed?

NewsIBRS advisor Dr Joseph Sweeney has been tracking the three major Cloud vendors capabilities in AI and said Google is right to believe it has an edge over AWS and Microsoft when it comes to corpus (the data that 'feeds' certain AI applications) and also in AI application infrastructure cost and performance. However, he said this advantage was not materialising into significant gains in the Australian market.

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Conclusion: Artificial intelligence technologies are available in various places such as robotic process automation (RPA), virtual agents and analytics. The purpose of this paper is to provide an AI maturity model in the analytics space. The proposed maturity model can be applied to any type of industry. It provides a roadmap to help improve business performance in the following areas:

  • Running the business (RTB): Provide executives with sufficient information to make informed decisions about running the business and staying competitive.
  • Growing the business (GTB): Provides information about growing the business in various geographies without changing the current services and products.
  • Transforming the business (TTB): Provides information to develop and release new products and services ahead of competitors.