IS ARTIFICIAL INTELLIGENCE EXPENSIVE?

TO MASTER AI AS A REVENUE CATALYST REQUIRES FIRST UNDERSTANDING ITS COSTS, WRITES SID BHATIA, REGIONAL VICE PRESIDENT, MIDDLE EAST & TURKEY, DATAIKU

Almost immediately after it became apparent that the world was changing under our feet, AI emerged as an enabler across the region. Suddenly, these technologies were not just being advocated by their vendors, but by analysts who pointed out that AI could help not only with battling the COVID pandemic, but in fomenting slick, robust economic recovery. Each industry could do something concrete to reinvent itself in the wake of seismic shifts in customer needs.

Analysis of economies across the Middle East and North Africa (MENA) predicts the region will respond dramatically to these arguments. By 2030, artificial intelligence will contribute 13.6% to the GDP of the United Arab Emirates and 12.4% to that of Saudi Arabia. And these are just the frontrunners. The Middle East as a whole is expected to be home to a US$320 billion AI industry by 2030.

The benefits of machine learning and advanced data analytics are now well known, but not everyone is enjoying success with these tools, because not everyone has the optimal migration methodology in place. If ingenuity does not flow quickly from AI investment, costs can outweigh gains before the technology has had a chance to add value. To prevent this, it is advisable to analyze each use case to see which

will add the greatest benefits in terms of productivity, operational efficiency, customer retention, and so on, and then price each of them to arrive at a costbenefit ratio.

Lower cost use cases can be leveraged to build trust in AI, by demonstrating value for each business stakeholder. But management of projects must happen at an umbrella level. Allowing unit heads to run their own projects in isolation can quickly lead to failure. Of course, this enterprise-wide AI approach hinges on being able to accurately analyse costs. So, what are the costs of AI? How can they be separated and examined in isolation?

Getting data ready

Data is food for AI. If not properly formatted (the industry term is “cleaned”) then your AI will choke. Value generation can only come from effective collation and preparation, which takes time, which represents a cost. Another term for this process is “data wrangling” — further indicating just how difficult and time-consuming this phase of the digital transformation project can be.

This is where the umbrella strategy will reap dividends. By taking an enterprise-wide approach to use cases, data can be warehoused on the same basis, meaning the organisation’s data-cleaning phase is implemented ALLOWING UNIT HEADS TO RUN THEIR OWN PROJECTS IN ISOLATION CAN QUICKLY LEAD TO FAILURE. OF COURSE, THIS ENTERPRISEWIDE AI APPROACH HINGES ON BEING ABLE TO ACCURATELY ANALYSE COSTS. SO, WHAT ARE THE COSTS OF AI? HOW CAN THEY BE SEPARATED AND EXAMINED IN ISOLATION?

once, bringing siloed stores together in a uniform fashion rather than having separate data-homogenising projects for each use case.

Deploying solutions

Moving to production brings several headaches, especially when each project may involve a variety of workflows and stakeholders. Operationalisation, therefore, can contribute greatly to costs, as development cycles spill over from weeks into months. Here, costs emerge not only from labor but from lost revenue because the solution is not in place in a production setting.

Solutions to these costs can be found in process optimisation. Consistency in the development lifecycle can serve all use cases. Creating these directives can be thought of like the datacleaning phase. If it is done properly in advance, it no longer arises as a concern in subsequent use cases. When development teams already know how to assemble and package code, and are well-versed in the formalities of releasing it, then business value can be added more quickly.

Acquiring and retaining talent

By getting the first two costs under control, the third becomes a more straightforward issue. The region is amid a skills crisis within the types of roles that typically deliver digital transformation. Data scientists and AI specialists are rare and expensive to attract. And while the cost of acquisition may be an externality that organisations cannot control, the retention or loss of such skills is entirely of their own making.

By ensuring repetitive tasks like data-cleaning are reduced to oneshot projects, enterprises create roles that are more about solving problems than about chore-like grinds. In this regard, proper resourcing will be a vital component of ensuring that an organisation need only acquire a skillset once, rather than having to spend money and time on repetitive recruitment.

Maintaining models and technologies

When data changes, the results from existing models may not tally with reality, leading to a potential cost, and such a cost applies (by varying degrees) to each use case. So-called MLOps can be a means of controlling maintenance costs, unifying the task across use cases. At the same time, AI technologies themselves are evolving and attracting different stakeholders to new capabilities. Again, if an organisation has kept its enterprise-wide strategy in place, it can more readily evaluate new business cases.

From cost centre to revenue source

The region’s innovators will struggle to realise the potential of AI if costs are poorly understood. As smart technologies take an evermore-prominent position among the economic activity of nations, enterprises must look for efficiencies in their implementation. By scaling with due diligence, winners will accrue benefits more reliably and ensure that AI becomes a source of revenue, rather than a drain on investment.

SEVEN TRENDS THAT CAN HELP MAKE THE MODERN ENTERPRISE MORE SECURE AND AGILE

SAJITH KUMAR, GENERAL MANAGER – ENTERPRISE FROM CLOUD BOX TECHNOLOGIES SUMMARIZES POSSIBLE TECHNOLOGY AND STRATEGIC MEASURES IN 2022 THAT CAN HELP TRANSFORM SECURITY FOR THE ENTERPRISE.

For the Boards of global and regional organisations, cybersecurity and managing digital transformation alongside, are promising to be amongst the most challenging. While Boards are doing a lot to bridge the gap between themselves and the CISO and the security organisation, here are some other technology and strategic measures that can help make the enterprise more agile and secure.

Trend #1 The big policy reset

What is the biggest and most immediate change required in an organisation’s security policies? It is the fact that majority of its employees are no longer employees but more like remote workers. Or in other words, remote workers are now the workers and remote work is now the organisation’s work. In other words, enterprises need to reset their entire security policies and tools to be able to manage risks from this new organisational reality.

Trend #2 ManaginzHow will security be deployed for the modern hybrid organisation, where workers are switching between multiple modes of working. At times they will be onsite inside the office firewall, at other times mobile and on the move, and at other times working from home. All the while accessing the wireless networks,

Internet or private VPNs. How will an organisation’s security architecture continuously adjust for its workers as they move across its fabric?

Today’s enterprises are being turned inside out with these challenges of managing workers requiring multiple modes and levels of security access. All organisations will need to have a defensive posture and well-defined security policies and risks with regard to onsite, remote and mobile workers.

One of the approaches is to develop and deploy a cybersecurity mesh, which enables a distributed enterprise to deploy and extend security where it is required the most.

Trend #3 Managing enterprise assets

Other than the pandemic, digital transformation is also responsible for connecting industrial, operational, IT assets that are distributed across the fabric of the organisation. These assets could be located at the edge, inside the network, at the core, and even inside other networks.

Gateways and middleware are now effectively and efficiently connecting disparate networks inside enterprises that were not feasible a decade ago. To manage all these challenges, security needs to be flexible, agile, scalable and yet robust enough to deliver for workers and protect for the organisation.

Trend #4 Just who is an employee?

As workers move across the enterprises’ security fabric, their security access levels need to keep changing. More importantly so should their identity-based security, with zerotrust being a dominant requirement. While zero-trust identity access is not new, it gains renewed importance in the face of hybrid worker access as well integration of disparate networks driven by digital transformation.

Social engineering to gain identity access is a dominant activity for sophisticated global threat actors. Hence, identity management techniques and practices need to be further elevated in terms of importance.

Along with human identities, we also have machine and robot identities, that are adding additional complexities in the overall identity access management operations. Digital technologies such as robotic process automation are driving automation of processes and each of these automated process or Bots requires a sign-on into the network and application stacks. APIs are another vulnerable hot spot where access is granted to users across multiple applications via APIs.

To better manage digital transformation, enterprises need to relook at their end-to-end identity credentials across all humans, Bots, devices.

Trend #5 Board improves communication

Boards are now alerted to address the challenges thrown up by ransomware, advanced persistent threats, and other supply chain malware that are having disastrous effects on some global businesses. Board members have been in the spotlight for being unable to speak the same language as CISOs and therefore unable to bridge the gaps from top to bottom. Now they are forming dedicated committees headed by security experts and selected board member to bridge the gap and address the challenge.

With this initiative, CISOs can expect much better information flow with the Board, as well as much deeper conversations about security spending, policies, proactiveness, risks and governance, strategy.

Trend #6 Proliferation of vendors

An ongoing challenge that continues into the next year is the complexity of security tools that are being managed by CISOs and IT managers. Global surveys by research firm Gartner have found that 78% of CISOs are managing 16 or more tools across their cybersecurity vendor portfolio. While 12% of CISOs are managing more than 46 tools.

The harsh reality is that cybersecurity organisations have far too many tools, from far too many vendors, leading to complex management routines, continuously high demand on skills and increasing security headcount.

Under these circumstances, CISOs need to begin extended vendor consolidation activities, realising that such activities take time and there is no short-term solution while heading in this direction. Another reality check is that reduction of capex spending may not be a direct, realisable benefit, but rather reduction of indirect costs and increase in operational efficiency are more achievable and realisable targets.

Trend #7 Testing and validation

New tools are being added to the portfolio of solutions that can be used to validate an organisation’s security vulnerabilities. One such area is breach and attack simulations that does continuous testing and validation of security controls and tests the ability to withstand external threats. It also highlights risks to high-value assets such as highly confidential data.

Another area that is developing is the ability to protect data while it is being read and used, in comparison to protecting data in motion or at rest. This enhanced security allows secure data processing, secure sharing, and cross border transfers without risks.