Perception and Use of Cloud Computing & Artificial Intelligence in the Adriatic Region Finance&Telco Sector 2018 Survey IDC

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1 Perception and Use of Cloud Computing & Artificial Intelligence in the Adriatic Region Finance&Telco Sector 2018 Survey

2 contents Executive Summary 3 Research Objectives 5 Key Analysis and Findings 6 Recommendations 23 Contact Information 24 Visit us at IDC.com and follow us on 2

3 Executive Summary Cloud adoption is set to grow steadiliy among financial and telco companies in Serbia, Croatia and Slovenia as 10 to 20% of the companies (depanding on the cloud type) are planing to implement cloud solutions within the next 12 months. 3 in 5 companies expect to become cloud native in two years time, meaning a widespread use of cloud across the company with strong leadership support and clear contribution of cloud to the business. When it comes to new IT functions 3 in 4 companies have a cloud also or a best fit approach, having no predefined barriers to choose public cloud. However, one third of the interviewed companies seem to be cloud resistant as they would not consider adopting cloud even if the functionality or services they are to implement is only available in cloud offerings. Providing more agility or speed to the business is the strongest business argument for cloud adoption, while end-off lifecycle replacements, upgrades, expansions, and re-platforming provide the best timing for swithcing to the cloud. Visit us at IDC.com and follow us on 3

4 Executive Summary Nearly one quarter of the banks interviewed are already using AI solutions for fraud and risk detection and management. The only application area with more frequent use of AI solutions is security and privacy due to the adoption of new generation security solutions with imbedded AI algorithms. Direct, indirect and online sales represent the business functions with the highest interest in investing in AI solutions in medium terms. Front- end business functions like marketing and customer services come next, while fraud and risk management will keep its potential for further adoption of AI solutions. Chatbots and AI enabled CRM solutions stand out as the AI solutions more than one third of the interviewed companies are planning to start using in the next 12 months. Robotic process automation software and intelligent assistants follow closely. Companies are lacking skills and expertise to implement AI solutions. Furthermore, the business decision makers are still looking for viable business cases of AI. This creates an opportunity for vendors to step into a consultant and delivery partner role. Moreover, many IT professionals question whether the technology is mature enough to justify implementation. A number of high-profile implementation failures have not helped in this regard. Visit us at IDC.com and follow us on 4

5 Key Analysis and Findings Visit us at IDC.com and follow us on 5

6 Cloud Implementation Status and Plans On average almost 4 in 5 of the interviewed companies are already using some form of cloud. Nevertheless the high adoption ratio will not lead to a slowing growth of the cloud market as 67% of the companies are planning to start using new type of cloud services in the next 12 months. There is a significant difference in cloud adoption between Innovator companies who characterise themselves as having a first to market mentality and Follower companies, which prefer to follow their peers. Innovator companies are using cloud to a significantly higher degree than followers and are also planning on expanding their cloud usage much more intensively than follower companies. Using Cloud Already Planing Using New Cloud Types Average Innovators Followers 78% 88% 67% Average Innovators Followers 67% 78% 5 6

7 Cloud Implementation Status and Plans Private cloud is the most popular form of cloud among the financial and telco companies interviewed. Public cloud is somewhat behind with slightly more then 2 in 5 companies already using it. The market is in a phase of shifting from internal private cloud to externally delivered hosted or public cloud. One third of the companies are planning to start using some form of hosted cloud in the next 12 months. Furthermore, more companies are planning to start using public cloud services than companies planning to implement private cloud services. While 78% of the companies are using some form of cloud (private, hosted or public) 44%c of them have already deployed a hybrid cloud. Private Cloud Hosted Cloud Public Cloud Using Planing No plans 61% 17% 33% Using Planing No plans 28% 33% 47% Using Planing No plans 44% 28% 50% 7

8 Cloud Implementation Status and Plans No particular form of cloud (private, hosted, public) stands out as significantly preferred over the other. The interviewed companies are quite flexible in which cloud form to adopt according to the best fit to their needs and many of them have already implemented multiple clouds. In one year from now half of the interviewed companies will have implemented private cloud architectures. SaaS stands out as the most preferred public cloud function, being nearly as widely accepted as private cloud. Hosted cloud seems to be the most popular delivery form for expanding cloud usage in the next 12 months. Quite a few SaaS and IaaS implementation can also be expected in the next 12 months hosted cloud Enterprise Private Cloud architectures Public software-as-a-service (SaaS) Container platform deployed on existing infrastructure Dedicated Hosted Private Cloud architectures Public infrastructure-as-a-service (IaaS) Public platform-as-a-service (PaaS) Container platform deployed on dedicated hosted infrastructure On-demand Hosted Private Cloud (Virtual Private Cloud) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Currently using Have firm plans to implement within 12 months Evaluating, but have no firm plans Not currently interested Don't know 8

9 Cloud Maturity Most companies interviewed expect to deploy a much more mature cloud strategy in the future. Only 1 in 4 companies believe they will maintain an ad-hoc or opportunistic approach to cloud. In two years time more than 3 in 5 companies foresee themselves as becoming cloud native with a widespread use of cloud across the company, strong leadership support and clear contribution of cloud to the business. To be able to execute on this ambition companies will need support to design their cloud strategies, roadmaps and implement them. 70% 60% 50% 40% 30% Ad Hoc or Too Soon to Tell Pilot projects or early stages of defining the cloud strategy. Opportunistic Repeatable Driven by the business needs of individual workgroups and departments. Consistent effort made to leverage best practices and resources across multiple groups and departments. 20% 10% 0% Ad Hoc or Too Soon to Tell Opportunistic Repeatable Managed or Optimized Managed or Optimized Widespread use of cloud, supported by proactive business and IT leadership or a cloud-native strategy broadly implemented which is clearly driving business. Today 24 months from today 9

10 Public Cloud Preference for New IT Services None of the interviewed companies have a public cloud first approach when they need net new IT capability, capacity or functionality. However, nearly 3 in 4 companies have a cloud also or a best fit approach, having no predefined barriers to choose public cloud as the delivery model for new IT functions. Innovator and Follower companies show very different profiles about their approach to cloud when they are looking for net new IT services. 45% of Innovator companies have a Cloud Also approach vs. only 13% in case of Followers. In change Followers are quite likely to have no consistent approach to cloud as a deployment model (38%). When we need new capability, capacity, functionality, Cloud First Cloud Also Best Fit Cloud Last Not defined We look to Public Cloud-based solutions first. We look to Public Cloud-based solutions at the same time as other traditional suppliers and software. When we select deployment model on a case by case basis within a defined selection process. We look to Public Cloud-based solutions only if we can't find what we need from other traditional suppliers and software. We have no consistent approach to the selection of Cloud vs. other deployment models. Cloud First Cloud Also Best Fit Cloud Last Not defined 10

11 Barriers for Faster Adoption of AI Solutions Talent shortage clearly represents the strongest barrier to more investment in AI. This creates an opportunity for vendors to step into a consultant and delivery partner role for AI and support companies in solving the AI resource and skills issue. Vendors can play a role in helping IT stakeholders make the case to C-level management as to the benefits of AI. While very few companies have concerns about the maturity of the technology, there is still a lack of understanding from the business of the value and potential of artificial intelligence or particular. Furthermore many companies are still looking for more convincing business cases. In general, providers of AI technology need to take a true partner role in the AI implementation process from proof of concept to trusted advisor throughout the lifecycle of the technology. Data privacy, governance and regulatory implications also represent a sizable obstacle as many companies have no experience around assuring compliance or data privacy security risks when it comes to using AI solutions. We don't have the skills or enough resources to implement the solutions we'd like In some areas we can't get the right business case Parts of the business don't understand AI and its potential We are worried about the data privacy / data protection issues We are worried about the governance and regulatory implications of using black box software models in some areas Some business leaders don't believe the technology is mature enough for us yet 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 11

12 Cloud Security Concerns Data privacy and loss of control over the data are the primary security concerns represent related to using cloud services. Data privacy Data loss/leakage Data sovereignty/control Availability of systems, services, and data Incident and problem management Liability Lack of forensic data/capability Exposure of credentials Other 0% 10% 20% 30% 40% 50% 60% 12

13 Cloud Security Challenges Compliance represents by far the biggest security challenge when it comes to using cloud. It represents a problem for more than two thirds of the companies interviewed. Consistency of security policies across an environment combining cloud and traditional architectures also represents a tough issue for two in five companies. On the operational sides of security the integration of cloud and on premises security solutions represent the major challenge. Legal and regulatory compliance Setting consistent security policies Integrating with on-premises security technologies Security keeping up with new applications or changes to existing applications Remediating threats Identifying misconfiguration Automating discovery/visibility/control of infrastructure Automating security enforcement across multiple datacenters LOB adherence to best practices, approved cloud apps and services 0% 10% 20% 30% 40% 50% 60% 70% 80% 13

14 Artificial Intelligence Implementation Status and Plans On average half of the interviewed financial and telco companies are already using some kind of AI solution. AI implementations are expected to accelerate as 71% of the companies are planning to start using new AI solutions in the next 12 months. The difference in the level of current adoption of AI solutions between Innovator and Follower companies is even more accentuated than is case of cloud. However the gap is closing when it comes to plans to implement AI in the next 12 months as Followers are taking a leap forward in initiating AI projects. Using Cloud Already Planing Using New Cloud Types Average Innovators Followers 53% 67% 38% Average Innovators Followers 71% 78% 63% 14

15 Business Areas Using AI/Cognitive Solutions Most companies are currently applying AI solutions in the area of security and privacy due to the adoption of new generation security solutions with imbedded AI algorithms. Nearly one in five company interviewed (80% being finance companies) are already using AI solutions in the area of fraud and risk detection and management and another one in three companies are planning to implement them. This is traditionally a prime area of using the latest in analytics with a high ROI levels. Front- end functions like marketing, customer services and online sales, with a high volume of customer engagement also represent a key application area in the present and with strong potential for the future. Direct, indirect and online sales represent the business functions with the highest potential for AI investments in medium terms. Back office functions, such as HR, payroll, legal or IT operations lag behind in acceptance of AI and are not among the top areas to see investments in AI in the future. All this despite the fact that respondents consider AI as being relevant for these business functions. IT operations security and privacy Marketing Finance fraud and risk detection and management Customer service Online sales and commerce Direct sales (via sales staff) and indirect sales (via partners) Finance operations IT operations helpdesk and support HR & payroll for transactional purposes Finance planning and management Legal HR for talent management 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Using now Planning to use Evaluating for future use No plans, but relevant for our business area No plans & not relevant for our business area 15

16 Data Quality While more than half of the interviewed companies are fully confident that the data supporting the decisions in their companies is relevant, only less than one third of them are fully sure about other quality criteria of their data, such as accuracy, up to datedness, completeness or consistency across the company. This leads to the conclusion that from a data quality perspective quite a few companies are probably ready for implementing AI for business process automation or decision support at the level of certain process phases or processes sequences or even on somewhat larger scale. However many companies should undergo a data quality assessment and improvement process to become fit in terms of the quality of their data assets for any larger scale AI strategy or implementation especially if historical data or more complex data is involved. Beyond data assessment, there is also an educational gap with respect to master and metadata management where vendors need to take on more of a consulting role. Innovator companies are much less satisfied with the quality of their company data than Followers. The reasons behind this difference may be related to the fact that Innovator companies are more data driven, their business models, processes and decisions relay more on data than the ones of Followers. Innovators have different needs in many aspect from the type of the data on customers, business performance, operations to higher expectations when it comes to relevancy, accuracy and consistency of data. Data supporting the decisions of our company is... Overall data quality on a scale from 1 to 5 (1 poor quality, 5 high quality) Relevant for the intended use Total Accurate and up to date Complete Followers/Conservative Consistent across the company Innovators 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Totally agree Somewhat agree

17 Adoption of AI Technologies Cyber-security applications represents the AI solutions with the highest current adoption. However when it comes to future plans for adoption the customer interaction and management solutions such as chatbots and AI enabled CRM are top of the list, followed by AI applications for fraud detection and risk avoidance. Few companies are using, planning to use or evaluating AI to augment existing applications or use to develop new ones themselves. This potentially means that companies regard AI as a fairly new domain that requires a break away from legacy applications to be implemented. Moreover buyers will turn to external solutions, consultants and developers to help them with their AI adoption plans. In the Adriatic region, as with the broader region of Central and Easter Europe, automation and risk mitigation are key motivators for AI adoption. Use cases aimed at customer satisfaction and quality of services, while popular in Western Europe and the US, are not major factors in the region. Cyber-security applications with embedded intelligence to deal with new threats 29% 24% 12% 29% Robotic process automation (RPA) software to handle transactional processes 24% 24% 18% 29% Financial applications with embedded intelligence for fraud detection and risk avoidance 18% 29% 18% 29% CRM applications with embedded intelligence for better business performance 12% 35% 24% 24% AI/Machine learning cloud services to augment our applications 12% 12% 12% 47% 18% AI/Machine learning algorithms to build applications and support business processes 12% 18% 59% Intelligent assistants for decision support 12% 24% 18% 35% 12% Chatbots for new customer interaction possibilities and improved customer engagement 47% 24% 18% Intelligent assistants for internal/external/customer enquiries and support 24% 24% 29% 18% Line of business specific applications with embedded intelligence 12% 24% 41% 18% Financial applications w embedded intelligence for better mngmt reporting and analytics 35% 47% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Using now Planning to use Evaluating for future use No plans, but relevant for our business area No plans & not relevant for our business area 17

18 Company Culture Related to Innovation More than half of the companies interviewed providing a good representation of the financial and telco industries in Adriatics see themselves as having a proactive, first to market mentality when it comes to innovation. Vendors should design their sales approach, messages and value proposition around cloud and AI taking into account the differences in maturity of Innovators vs. Followers/Conservatives. Innovators nurture a favourable business culture for being early adopters or scalers of solutions like cloud and AI, as they are looking for investing in innovative solutions as a tool to create competitive advantage. Our Company Culture for Innovation Company profile (Innovators vs. Followers/Conservatives) Innovators Followers/Conservative Overall data quality (5 and 4 rankings) Implementing new AI solution in the next 12 months Cloud adoption 100,00% 75,00% 50,00% 25,00%,00% Hybrid cloud adoption Implementing new cloud in the next 12 months First to market mentality Following our peers Highly conservative AI adoption "Cloud also" approach 18

19 Recommendations for Vendors 1 Cloud adoption has become widespread among financial and telco companies and cloud as an alternative scenarios are becoming mainstream. Vendors should position their cloud offering into the wider context of providing the platform for digitalising the company, including its processes, products and services with the goal to increase flexibility, agility, shorten time to deploy and market. Nevertheless vendors should address the still persisting or evolving security concerns of the companies, such as GDPR compliance of their cloud offering. 2 Most companies have a hybrid cloud approach opting for a combination of private, public and hosted cloud depending on the best fit to their needs for services, cost expectations and preferences of keeping control over applications and data. Vendors that have solutions with seamless integration into a hybrid environment will have a competitive advantage. 3 AI is likely to quickly move into accelerated adoption stage in the finance and telecoms sectors. For vendors wishing to secure their position in this market now is the time for more focus, investment and resources as an increasing number of companies have plans to start using AI in various application areas. Demonstration of skills and success stories are the first step toward client acquisition. 4 Vendors should be ready for more requests from companies for external solutions, consultants, developers and implementation partners to help them with their AI adoption plans as many of them are lacking the skills expertise and resources. In general, vendors of AI technologies must be much more than technology providers. They should strive to be advisors, consultants and partners that can work with their clients from early stages of consideration, to pre-implementation preparation, integration and subsequent adjustment and modification. Without this partnering approach market potential cannot be realized. 4 Vendors should consider segmenting their customers into Innovators and Followers as our research suggests these companies have a quite different profile in terms of their maturity and readiness to invest in innovative technologies such as cloud, AI/cognitive solutions or improving the quality for their company data. Due to the different profile Innovators will likely need less sales effort to be convinced and are in a more advanced stage of the customer life-cycle as they need less education and more information for purchase decision, building their business cases and successfully execute implementations. Visit us at IDC.com and follow us on 19

20 Authors Zoltan Komaromi AVP, Reserach & Consulting IDC CEE Mobile: IDC Hungary Tűzoltó utca 57 Budapest Hungary Zorana Juric Regional Manager Adriatic IDC CEE Mobile: IDC Serbia & Montenegro Bulevar Zorana Đinđića 71 Belgrade Serbia