Author: altilia

The demand for AI-based solutions in the enterprise is ever increasing as more and more companies view artificial intelligence as a solution to automate core business process, driving operational excellence and accelerating digital transformation.

Top-level research from the Artificial Intelligence Observatory of the Polytechnic University of Milan shows that, from a sample of 200 large organizations operating in Italy, 59% have already started executive projects in the AI field, 77% of which are running more than one project in parallel.

According to a recent survey by PwC in US, on a sample of 1000 large organizations, 72% have already integrated or are looking to integrate AI technologies into their operations.

Full-scale deployment

Deloitte’s significant State of AI study found that 79% of business leaders surveyed reported full-scale deployment for three or more types of AI applications – up from 62% in the previous year. And 76% of those leaders expect AI investments to increase in the next year.

But not everything in the AI garden is rosy, particularly for small and medium sized organisations.

There are many challenges affecting the effective use of artificial intelligence which can hinder the ability to tap into its potential and lead to a growing gap between those companies that have the capability and those who do not.

Over two blogs, we will focus on the two big challenges facing organisations planning to use AI – and how Altilia can make the difference.

1. The AI skills shortage
2. The complexity of managing Machine Learning Operations

The AI skills shortage

McKinsey’s State of AI 2022 Survey called out the difficulties of hiring AI-related roles, with 78% of respondents citing difficulty with hiring AI data scientists, 72% struggling to hire data architects, 70% ML engineers and 69% data engineers.

Perhaps surprisingly, they state that finding AI hires is perceived as more difficult than three years ago, with 57% saying that the hiring of data engineers is more difficult, 52% for data architects and 48% of ML engineers.

Clearly, demand for top AI talent is outstripping supply.

Among the limiting factors, the skills problem emerges as one of the most relevant. In addition to programming and software development skills, the planning and life-cycle management of an AI project, requires highly specialized skills that are still scarcely available in the labour market.

These technical skills include:

• Skills needed to identify and prepare datasets that will be used by AI algorithms.
• Mathematical and statistical skills that enable the solving of complex problems related to AI applications.
• Skills needed to implement Machine Learning and Deep learning models (e.g., Supervised & Unsupervised Learning techniques).
• Skills related to data storage infrastructure, cloud services, and integration of AI systems with other enterprise software and applications.

In addition, since AI automation projects are ultimately aimed at boosting operational business processes, it is crucial to create a match between AI skills and all the skills involving the application of specialized domain-specific knowledge, methodologies, and operational techniques for the operation of specific areas, such as Supply Chain, Marketing and Sales.

For this reason, a core challenge is to bridge the gap between technical AI skills and domain-specific competences within companies and bringing core AI skills to figures not traditionally related to engineering and software development.

How can Altilia help to overcome the skills gap challenge?

Altilia prioritizes AI democratization as the core of its approach: for this reason, the Atlilia Intelligent Automation platform is designed to maximize intelligent process automation capabilities while minimizing the complexity of managing AI algorithms for the end user.

• Thanks to the use of pre-built algorithms, based on transformer models, users can leverage AI capabilities even without the in-depth mathematical and statistical knowledge related to AI applications.
• Thanks to the use of a no-code visual interface for document annotation and review, users can autonomously prepare the dataset that will be used by AI algorithms, even without the technical skills required to implement machine learning or deep learning models.
• Altilia’s IPaaS cloud infrastructure, equipped with pre-built software connectors, greatly simplifies software interoperability, and removes the complexity of managing computing resources and data storage.

In addition, the Altilia Intelligent Automation platform is designed for to reduce the learning curve for business-domain experts to understand and apply AI algorithms for business automation.

In fact, the Altilia Labels module for document annotation, allows business-line users to intuitively transfer their knowledge into algorithms, to perfectly fine-tune the solution according to real business and process needs.

The Altilia Reviews module provides a tool to review and validate the results produced by the algorithms, this is a crucial feature to guarantee AI explainability and to allow business-line users to effectively govern the process.

Contact us here to discuss how Altilia can support your organization’s drive for business optimization through AI.

And read our next blog on the challenge of managing ML Ops.

As 2022 is coming to an end, we want to take a step back and have a look at the state of the industry of AI for business automation.

McKinsey has just published their “State of Artificial Intelligence 2022” report, based on a survey of from 1,492 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures.

The report demonstrates the growth and importance of AI to organizations, with a set of companies seeing the highest financial returns from AI continuing to pull ahead of competitors.

The results show these leaders making larger investments in AI, engaging in increasingly advanced practices known to enable scale and faster AI development, and showing signs of faring better in the tight market for AI talent.

There were two key takeaways from this important report:

1. AI adoption is increasing, and the market is growing.
2. Emerging AI leaders are reaping the rewards.

AI adoption is increasing, and the market is growing

Global AI adoption is increasing: companies adopting AI in at least one business area increased by 2.5 times since 2017. The average number of AI capabilities used by organizations has increased from 1.9 in 2018 to 3.8 in 2022.

Investments in AI have also increased: % of companies whose digital budget went for more than 5% to AI increased from 40% in 2018 to 52% in 2022.

Most used embedded capabilities:

• Robotic Process Automation 39%
• Computer Vision 34%
• Natural Language Processing 33%
• Deep Learning 30%
• Knowledge Graphs 25%
• Reinforcement Learning 20%
• Transformers 11%

Altilia is exceptionally well positioned, since its offer is strong for both widely adopted embedded capabilities (RPA, Computer Vision, NLP) as well as new emerging capabilities whose value is not yet fully understood by the market but will become critical in the coming years (Knowledge Graphs, Reinforced Learning, Transformers).

With companies starting to understand the cross-functional potential of AI automation application, this also puts Altilia in a good position as the Altilia Intelligent Automation platform is designed to let customers leverage the same infrastructure to implement multiple use cases. This helps to increase the ROI of the platform over time.

Emerging AI leaders are reaping the rewards

McKinsey recognizes a group of “AI high performers”, a group of companies that are being particularly effective with the implementation of AI projects. Companies whose EBIT have increased more than 20% from the use of AI (8% of total respondents).

These high performers are more likely than others to follow ‘frontier’ core practices that unlock value:

• Adopting practices for AI development at scale (AI Ops).
• Embracing modular AI architecture to rapidly accommodate new AI applications.
• Introducing quality control procedures to provide high-quality data to feed AI algorithms.
• Leverage emerging low-code and no-code programs to speed up the creation of AI applications.

These AI high performers are also more likely than other companies to report that they engage in practices to mitigate AI related risks, testing the validity of models and monitoring them over time for potential issues.

Altilia is again well positioned since Altilia Intelligent Automation is designed to let customers ‘outsource’ the complexity of AI Ops, a topic we will investigate further in a subsequent blog post.

Our platform has a modular architecture and it allows to simplify the deployment of multiple AI applications, and it’s also designed as a low-code/no-code platform, to simplify the creation of AI applications.

It is important to understand that Altilia Intelligent Automation combines the use of Large Language Models (LLMs) with no-code technology, and this constitutes a breakthrough.

LLM are already popular and publicly discussed, but those are general purpose technology that doesn’t perform very well for specific business applications.

By utilizing Altilia’s no-code approach to AI models training, these ‘general purpose’ technologies can be fine-tuned by enterprises, to turn them into a ‘domain-specific’ technology.

This will allow businesses of all sizes to experience the benefits of LLM technology in their specific business applications, allowing them to obtain returns on AI investments, comparable to the “high performers” mentioned by McKinsey.

The magical promise of artificial intelligence is that it learns as it goes along and develops additional data insights that enable your organization to make rapid progress.

Now Adaptive AI has been identified by Gartner as one of the top 10 emerging trends for 2023, taking AI capabilities to the next level where it is able to absorb learnings even as it’s being built.

They estimate that by 2026, enterprises that have adopted AI engineering practices to build and manage adaptive AI systems will outperform their peers in the operationalizing AI models by at least 25%.

In a recent Gartner article, they write: “Adaptive AI brings together a set of methods (i.e. agent-based design) and AI techniques (i.e. reinforcement learning) to enable systems to adjust their learning practices and behaviors so they can adapt to changing real-world circumstances while in production.”

What is Adaptive AI?

So, what is Adaptive AI and how does it differ to our current understanding of how AI works?

The key is that Adaptive AI can revise its own code to adjust for changes that weren’t known or predicted when the code was first written, enabling adaptability and resilience to be built into the design so that it can react immediately to changes.

It means that the “learning” phase of a traditional AI system can be bypassed so that the AI is effectively learning whatever is happening.

The value of operationalized AI lies in this ability to rapidly develop, deploy, adapt and maintain AI across different environments in the enterprise.

AI models with this self-adaption built in can develop quicker and with less errors. It creates a faster and more superior user experience by adapting to changing real-world situations.

Altilia at the forefront

Altilia is at the forefront of this approach to optimizing artificial intelligence to take it to the next level.

In our platform, we use reinforcement learning to improve the accuracy of our machine learning models over time.

Also, as a method, we have designed a human-in-the-loop feedback cycle that allows users to trace back the extracted data points to the original source (i.e. the exact position within the document).

This allows them to validate data, and the resulting feedback is taken into consideration to re-train the AI model. In this way the model can improve their accuracy over time and prevent data drifting.

It also means that if the format or layout of the processed documents is gradually modified over time, the algorithm is capable of adapting without the need to refactor our solution.

Why not schedule a demo of Altilia’s ground-breaking AI intelligent document processing solutions and see how it can revolutionize your organisation’s use of your data?

You can sign up here for your demo. 

HyperAutomation (HA) is rapidly moving from just being an interesting proposition for highly innovative projects and applications to becoming a critical business need for organizations across any industry.

Today, and in the coming months, the threat of possible recession scenarios, demands businesses make greater efforts to improve their cost efficiency, agility, productivity, and innovation-based resilience.

According to a recent forecast by Gartner, by 2025 the HA software market is expected to reach a market value of nearly $860 billion worldwide, with a Compound Annual Growth Rate (CAGR) of 12.3%.

Massive impact

In this scenario, the impact of Intelligent Document Processing (IDP) platforms that are capable of integrating hybrid AI approaches based on computer vision, Neuro-linguistic Programming (NLP), knowledge representation, rule-based methods, and other AI technologies, will be massive.

These platforms will accelerate digital transformation across most verticals, with highest adoption rates in industries like financial services (banking, insurance, investing etc.), telecommunications, media, utilities, manufacturing, and services.

Use case applications will provide:

• Improved personal and organizational efficiency,
• Improved user interactions and satisfaction of both customers and employees,
• More efficient and agile work methods,
• Improved Robotic Process Automation (RPA) application potential for processes requiring human cognitive capabilities,
• Enhancements and performance improvements for pre-existing software solutions and systems within the organization, like RPA, ECM, ERP, CRM.

Companies are increasingly experimenting and implementing solutions based on Intelligent Document Processing (IDP) and Intelligent Process Automation (IPA) approaches and tools.

In parallel, we are witnessing a growing interest in Hybrid and Composite AI solutions that enable close interactions between machine and human intelligence, by combining semantic and ML approaches with no-code/low-code and conversational user interfaces (CUIs).

This paradigm shift is enabling organizations to gradually change their approach for the automation of operational and decision-making tasks, involving business users more closely in the process.

At this rate, in the next 3 to 5 years we expect some of the most advanced IDP capabilities to become a standard market requirement.

This includes:

• The capability to ingest and process documents and contents from several different unstructured sources and in various formats.
• Semantic document and data indexing capabilities.
• Interfacing and interoperating capabilities with other applications in the customer’s software ecosystem.
• The ability to manage end-to-end business processes automation as a comprehensive suite or in tandem with other RPA solutions

Additionally, in the companies where the RPA revolution is already taking place, we expect progress to move forward only as these solutions will become increasingly integrated with IDP platforms, in order to unlock the untapped potential of automating processes involving the handling of unstructured data present in documents, texts and other unstructured sources.

These are exactly the kind of capabilities Altilia is pushing forward with the Altilia Intelligent Automation™ platform, setting the bar for end-to-end IDP platforms technological advancements.

Over the next 3 to 5 years, Altilia will continue to address the increasingly complex HyperAutomation needs of organizations, acting as a strategic partner to facilitate customers’ strategic investments in HA/IPA/IDP initiatives, from the simplest tactical implementations to the more disruptive and valuable innovations.

For more information on how HyperAutomation can transform your business, contact Altilia here .

As we have seen, HyperAutomation (HA) is becoming an important strategic trend for organizations seeking to rapidly identify and automate the latest possible number of business processes to drive efficiency, agility and productivity.

The HA label, as identified by Gartner, brings together a range of AI and automation technologies – and, most importantly, a determination to break away from a siloed approach to address multiple labour-intensive workflows holistically.

Typical use case applications for Intelligent Document Processing (IDP) and Intelligent Process Automation (IPA) technologies can be found in both front and back office processes of organizations of any size in any industry, including Public Administration.

Some typical use cases include the following:

• Banking and Insurance customer onboarding operations that require the reading of ID documents, financial documents and income statements.
• File verification and validation in Public Administration, requiring data extraction from very large and varied sets of documents.
  In the field of legal contract management, support for terms and clauses interpretation and verification.
• Automated reading and classification of contents from regulatory compliance reports for Risk Management and Internal Audit purposes.
• Automating procurement and sales operations processes, like reading and extracting data from orders, payments, contracts, invoices and bills, is becoming an increasingly common practice.

Some even more advanced use case scenarios include:

• Automated documents and images processing for insurance claims management.
• Automated data collection from balance sheets, notes to balance sheets, business plans and financial statements for credit scoring purposes in the mortgage and lending management process.
• Automating ESG (Environmental Social & Governance) company profiling, based on the information and data extracted from multiple sources, like annual reports, sustainability reports, websites, news, etc.
• Supporting NPL (Non-Performing Loan) and UTP (Unlikely To Pay) portfolio evaluation, by automating data extraction and collection from complex documents for the effective assessment of distressed credit.
• Automated reading of medical records and clinical trial results for patient management and new drugs development in the Healthcare and Pharma industries

Typically, the end-goal of these applications is to drastically reduce the manual work time required to read and interpret documents, to cut down data entry operations and to enable automatic verification procedures in support of sophisticated operational and decision-making processes.

A comprehensive IDP solution such as the Altilia Intelligent Automation™ platform can bring important advantages both in terms of efficiency and cost reduction, leading to end results often exceeding a 100% ROI, based on the total costs of ownership.

This is possible as an organization gains the ability to:

• Speed-up business processes by up to 10 times.
• Upscale document processing capabilities, according to real data volumes and business needs.
• Reduce manual errors and oversights.
• Drastically reduce the manual work (often by more than 80%).
• Improve employee satisfaction, by reducing the time spent on tedious and repetitive manual tasks (like data entry, document reading and inspection).
• Improve customer satisfaction as processes are handheld more quickly and accurately.
• Increase overall margins, as the improved access to data and information allows business leaders to make more informed and timely decisions.

For Altilia’s customers, an IDP platform represents a strategic investment to meet all their HA needs arising over time, allowing them to both scale up existing use cases to meet increasing business demand, as well as creating and deploying new domain-specific use cases with a unified approach.

To learn more and have a chat with Altilia’s automation experts, contact us here.

Rende/Milan, July 25th, 2022. Altilia, the Italian deep-tech company has been included in the first Gartner® Market Guide report on Intelligent Document Processing, published in February 2022 (1).

Altilia Intelligent Automation™ has been included among other representative vendor’s solutions. In another 2021 Gartner report (2) Altilia was listed among the representative IDP software provider among other companies competing in a fast-growing market.

In that same report, outlining the IDP competitive landscape, Gartner underlined the role of Unstructured data specialists.

“These are new providers in the IDP space, mostly sprung up in the last five years or so. They are usually venture capital (VC)-funded companies. Their key value proposition is that they have an AI-led approach to focus primarily on semistructured and unstructured data (often a strong focus on handwritten documents) that is their core value proposition. They mostly partner for OCR engines”. (2)

Defining the IDP market, in its first report specifically focused on Intelligent Document Processing solutions Gartner states that;

“Intelligent document processing (IDP) solutions extract data to support automation of high-volume, repetitive document processing tasks and for analysis and insight. IDP uses natural language technologies and computer vision to extract data from structured and unstructured content, especially from documents, to support automation and augmentation”.(1)

According to this Gartner’s February 2022 report, Altilia currently mostly serves industries : “Banking, insurance, utilities, retail, securities” and list most commonly process documents for Altilia: “Annual/sustainability/interim/financial reports, balance sheets, Invoices, orders, Social media posts, news, bank statements, paychecks”

Gartner lists ‘Establishing a Marketplace as a Viable Channel in Their Go-to- Market’ as one of the competitive trends about IDP Competitive Landscape

The report observes “early signs of establishing the marketplace as a channel as part of the go-to-market (GTM) approach of the IDP vendors”.(2)

Altilia is among a small numbers of vendors developing their own marketplaces.

This means transitioning from the traditional approach (bespoke project with project and implementation times and costs) to a ‘out of the box’ approach with bundled solutions ready to use.

Altilia’s team of 40 Scientists, Engineers, Innovators, Growth Hackers are building a no-code SaaS platform, that democratizes the adoption of AI, hyperautomation and decision intelligence for large corporations and SMEs in Finance and a number of other industries. This platform will be available also as a tool from the Altilia.ai website and will be exploitable from day 1 with a minimum of training without any knowledge of AI.

Reference

1. Gartner “Market Guide for Intelligent Document Processing Solutions” Shubhangi Vashisth, Anthony Mullen, Stephen Emmott, Alejandra Lozada, February 2022

2. Gartner, “Competitive Landscape: Intelligent Document Processing Platform Providers,” Arup Roy, Arthur Villa, Cathy Tornbohm, Soyeb Barot, November 8, 2021.

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