Rethinking innovation policy for economic growth

An economy can spend billions on research, build technoparks, open laboratories, and launch dozens of innovation support programs. Yet growth remains weak. Productivity barely moves. Knowledge exports stay limited. New companies fail to scale. This is not a paradox and not a statistical glitch. It is a systemic problem of innovation policy at the technological frontier.

The key trend of recent years is clear. Countries that have already caught up with advanced economies in terms of technology no longer get automatic returns from higher R&D spending. Money stops working on its own. What matters is not the size of funding, but how the innovation machine is built. Who selects projects. How risk is assessed. What counts as success. And how knowledge reaches the market.

This shift is especially important for Kazakhstan. The country has already passed the phase of simple technology borrowing. Industrial programs delivered infrastructure and capacity. But the next step is harder. It requires a different logic of innovation policy. Stricter. More mature. And less bureaucratic.

At the frontier, the innovation system looks solid from the outside. High R&D budgets. Active state involvement. A wide network of institutes, agencies, and programs. Formal transparency. Detailed reporting. But inside, distortions build up. Money is allocated carefully, but cautiously. Projects are selected to avoid failure. Mistakes are punished more harshly than the absence of results. Economic impact gets lost between the lab and the market.

The core problem starts with evaluation. R&D selection and control systems are used to counting inputs and outputs. How many projects were launched. How many reports submitted. How many patents registered. How many papers published. These indicators are easy to verify. Convenient for KPIs. They create an impression of progress. But they say almost nothing about economic growth.

The economy does not run on publications or patents. It runs on sales, scaling, market entry, and the displacement of old technologies. This is where the system begins to stall. Projects can be formally successful and still have no future. Others can be risky and promising, but fail to pass selection.

At the innovation frontier, risk becomes the key currency. Without it, there are no breakthroughs. But bureaucratic logic does not tolerate risk well. It demands predictability. It prefers projects that can be safely defended in committees. Those where outcomes are known in advance. As a result, money flows to places where the chance of failure is lowest. And where the chance of radical impact is also lowest.

This bias is familiar in Kazakhstan as well. The innovation support system is built so that a safe project beats a bold one. A project with a polished presentation beats one with an uncertain market. Teams that can talk win over teams that can build. In the short term, this reduces scandals. In the long term, it kills growth.

Another weak point lies in the selection logic itself. Projects are often designed top-down. Priorities are set in advance. Topics are defined at agency level. Implementers are selected later. This approach works when the state commissions research for its own needs. But it fails where innovation should come from business and researchers. Ideas stop competing. They are adjusted to fit templates.

The innovation market works differently. The best ideas rarely emerge within pre-approved themes. They arise at the intersection of disciplines. In small teams. In response to real demand. When the system first selects the topic and only then looks for performers, it loses spontaneity. And with it, the chance of a breakthrough.

Another problem is the process itself. Evaluation takes months. Committees. Approvals. Hearings. But little time is left for the actual teams. Decisions are often made quickly, based on slides and Q&A. Deep individual expertise is limited. Feedback loops are weak. A project is either approved or rejected. In such a system, risk does not disappear. It is simply disguised. Projects look neat. But economic impact remains weak. This is the main reason why higher R&D spending does not equal higher economic growth.

Commercialization is where the gap becomes most visible. Universities and research institutes actively produce knowledge. Companies look for ready solutions. But between them lies a void. Weak incentives. Low trust. Different languages. Academia lives by its own rules. Publications. Citations. Grants. Careers. Business lives differently. Deadlines. Risk. Control over intellectual property. Money. When these worlds meet without the right institutions, cooperation fails.

Businesses are often unwilling to invest in developments they do not own. Universities are reluctant to give up control over results. Public institutions get stuck in between. Technologies end up on shelves. Or move abroad. Or never reach the market. Commercialization requires its own infrastructure. Not formal, but practical. People who understand markets. Who can turn technology into a product. Who can honestly say an idea will not fly – and shut it down in time. Without this, even strong research stays academic.

Time is another systemic distortion. Innovation does not follow budget cycles. Commercialization rarely fits into two or three years, especially in knowledge-intensive sectors. But support programs often demand fast results. This pushes teams toward shallow solutions. Demo effects. Reports instead of products. At the frontier of the knowledge economy, time becomes a strategic resource. Compressing it comes at a cost. Countries that ignore this end up with an innovation showcase without substance. For Kazakhstan, the lesson is direct. Innovation policy cannot be a copy of industrial policy. It requires a different tolerance for uncertainty. Different metrics. Different people in the system.

Human capital is another key part of the innovation machine. Not the number of diplomas, but how knowledge moves across sectors. In advanced systems, students and young researchers regularly work in companies. Write theses around real problems. Return to universities with market experience. These links create trust and channels for commercialization. Where such links are missing, the innovation system closes in on itself. Projects are reproduced for the sake of projects. Growth stops.

This gap is visible in Kazakhstan too. Universities and business often exist in parallel. Joint projects are formal. Young specialists lack market experience. Companies see little value in academic research. This is not about culture. It is about institutions and incentives.

Public research institutes play a special role. In the catch-up phase, they were essential. They helped absorb technologies, adapt knowledge, and close gaps. But at the frontier, their mission changes. Some must focus on fundamental research. Others must become contract R&D partners for business. When everyone does everything, efficiency falls.

Intellectual property is another constraint. On paper, protection exists. But business looks at practice. Speed. Court quality. Predictability. If protection is weak or uncertain, investment does not come. This slows commercialization more than any tax. Against this background, simple solutions become tempting. Increase funding. Launch new programs. Create another fund. But without changing system logic, the outcome stays the same. More money flows through the same filters. With the same results.

Real reform of innovation policy does not start with budgets. It starts with questions. What counts as success. Who takes risk. How failed projects are closed. Who is responsible for market transition. How economic impact is measured. This is especially relevant for Kazakhstan now. The country is stuck between two models. The old industrial growth model no longer delivers. The new knowledge economy model has not started working yet. Innovation policy becomes a point of choice.

One path is to keep expanding formal indicators. More programs. More R&D spending. More infrastructure. The other is to rebuild the innovation machine itself. Make it less safe, but more effective. Less about reporting, more about markets. Less closed, more connected to business. At the frontier, winners are not those who spend more. They are those who select better, learn faster, and shut down failures honestly. It is a tough lesson. But without it, the knowledge economy does not work.

Aidar Kakimzhanov, independent expert, specifically for www.economyKZ.org